Disclosure of Invention
The embodiment of the invention provides a method for selecting addresses of a logistics distribution point, which reduces the operation pressure of the distribution point and improves the efficiency of selecting addresses of the distribution point by separating the operations of collecting goods and bulk goods to different network nodes, so that the address selecting results of a distribution area are more comprehensive.
In one aspect, the application provides a method for selecting a physical distribution point, which comprises the following steps:
Acquiring logistics network information in an area to be planned, wherein the logistics network information comprises a lower logistics network point set, a candidate collection point set and a candidate bulk cargo point set in the area to be planned;
generating a virtual distributed area set according to the logistics network information;
and optimizing each virtual distribution area in the virtual distribution area set to obtain an optimal distribution area, wherein the optimal distribution area comprises at least one collection point and at least one bulk point.
In some embodiments of the present application, the generating a virtual distributed patch area set according to the logistics network information includes:
Generating a virtual distribution area set according to the candidate collection point set and the candidate bulk point set, wherein the collection points in the candidate collection point set and the bulk points in the candidate bulk point set belong to at least one virtual distribution area in the virtual distribution area set;
And placing each lower-level logistics network point in the lower-level logistics network point set into a virtual distribution area of the virtual distribution area set, so that each lower-level logistics network point in the lower-level logistics network point set belongs to one virtual distribution area in the virtual distribution area set.
In some embodiments of the present application, the generating a virtual distributed patch area set according to the candidate set of cargo points and the candidate set of bulk cargo points includes:
sequentially selecting one collection point from the candidate collection point set, selecting one bulk point from the candidate bulk point set, and constructing collection and distribution point pairs;
And generating a virtual distribution area for the distribution point pair until the collection points in the candidate collection point set and the bulk points in the candidate bulk point set belong to at least one virtual distribution area.
In some embodiments of the present application, the placing each lower-level logistics dot in the lower-level logistics dot set into a virtual distribution area of the distribution area set, so that each lower-level logistics dot in the lower-level logistics dot set belongs to one virtual distribution area in the virtual distribution area set, includes:
Randomly selecting a lower-level logistics network point from the lower-level logistics network point set in sequence, and randomly selecting a virtual distributed patch area from the virtual distributed patch area set;
And placing the currently selected lower-level logistics network points into the currently selected virtual distributed patch area until each lower-level logistics network point in the lower-level logistics network point set belongs to one virtual distributed patch area in the virtual distributed patch area set.
In some embodiments of the present application, the optimizing each virtual patch panel in the set of virtual patch panels to obtain an optimal patch panel includes:
the attribution relation of the lower logistics network points of each virtual distributed area in the virtual distributed area set is adjusted according to preset constraint conditions, and the virtual distributed area set after adjustment is obtained;
Respectively taking each virtual distributed area in the adjusted virtual distributed area set as a target virtual distributed area, and calculating the sum task programmable time length, the overtime task number, the sum task mileage and the sum transportation cost corresponding to the target distributed area;
And optimizing each virtual distributed area in the virtual distributed area set according to the adjusted total task planning duration, the number of overtime tasks, the total task mileage and the total transportation cost corresponding to each virtual distributed area in the virtual distributed area set to obtain the optimal distributed area.
In some embodiments of the present application, the optimizing each virtual distribution area in the virtual distribution area set according to the adjusted sum task programmable duration, the number of overtime tasks, the sum task mileage and the sum transportation cost corresponding to each virtual distribution area in the virtual distribution area set to obtain an optimal distribution area includes:
Determining a first virtual distributed area with the minimum overtime task number in the overtime task number corresponding to each virtual distributed area in the adjusted virtual distributed area set;
determining a second virtual distributed patch area with the longest sum of the programmable durations in the first virtual distributed patch area;
Determining a third distributed patch area with the shortest total task mileage in the second virtual distributed patch area;
Determining a fourth distributed patch area with the lowest total transportation cost in the third distributed patch area;
And determining the fourth distributed patch area as an optimal distributed patch area.
In some embodiments of the present application, before the optimizing each virtual patch panel in the set of virtual patch panels to obtain an optimal patch panel, the method further includes:
Constructing a distributed area site selection model;
optimizing each virtual distributed patch area in the virtual distributed patch area set to obtain an optimal distributed patch area, wherein the optimizing comprises the following steps:
And optimizing the virtual distributed patch area by using the distributed patch area site selection model to obtain the optimal distributed patch area.
In another aspect, a device for locating a distribution point of a stream, the device comprising:
The system comprises an acquisition unit, a planning unit and a storage unit, wherein the acquisition unit is used for acquiring logistics network information in an area to be planned, and the logistics network information comprises a lower logistics network point set, a candidate collection point set and a candidate bulk point set in the area to be planned;
the generation unit is used for generating a virtual distributed area set according to the logistics network information;
and the optimizing unit is used for optimizing each virtual distribution area in the virtual distribution area set to obtain an optimal distribution area, and the optimal distribution area comprises at least one collection point and at least one bulk cargo point.
In some embodiments of the present application, the generating unit is specifically configured to:
Generating a virtual distribution area set according to the candidate collection point set and the candidate bulk point set, wherein the collection points in the candidate collection point set and the bulk points in the candidate bulk point set belong to at least one virtual distribution area in the virtual distribution area set;
And placing each lower-level logistics network point in the lower-level logistics network point set into a virtual distribution area of the virtual distribution area set, so that each lower-level logistics network point in the lower-level logistics network point set belongs to one virtual distribution area in the virtual distribution area set.
In some embodiments of the present application, the generating unit is specifically configured to:
sequentially selecting one collection point from the candidate collection point set, selecting one bulk point from the candidate bulk point set, and constructing collection and distribution point pairs;
And generating a virtual distribution area for the distribution point pair until the collection points in the candidate collection point set and the bulk points in the candidate bulk point set belong to at least one virtual distribution area.
In some embodiments of the present application, the generating unit is specifically configured to:
Randomly selecting a lower-level logistics network point from the lower-level logistics network point set in sequence, and randomly selecting a virtual distributed patch area from the virtual distributed patch area set;
And placing the currently selected lower-level logistics network points into the currently selected virtual distributed patch area until each lower-level logistics network point in the lower-level logistics network point set belongs to one virtual distributed patch area in the virtual distributed patch area set.
In some embodiments of the present application, the optimizing unit is specifically configured to:
the attribution relation of the lower logistics network points of each virtual distributed area in the virtual distributed area set is adjusted according to preset constraint conditions, and the virtual distributed area set after adjustment is obtained;
Respectively taking each virtual distributed area in the adjusted virtual distributed area set as a target virtual distributed area, and calculating the sum task programmable time length, the overtime task number, the sum task mileage and the sum transportation cost corresponding to the target distributed area;
And optimizing each virtual distributed area in the virtual distributed area set according to the adjusted total task planning duration, the number of overtime tasks, the total task mileage and the total transportation cost corresponding to each virtual distributed area in the virtual distributed area set to obtain the optimal distributed area.
In some embodiments of the present application, the optimizing unit is specifically configured to:
Determining a first virtual distributed area with the minimum overtime task number in the overtime task number corresponding to each virtual distributed area in the virtual distributed area set;
Determining a first virtual distributed area with the minimum overtime task number in the overtime task number corresponding to each virtual distributed area in the adjusted virtual distributed area set;
determining a second virtual distributed patch area with the longest sum of the programmable durations in the first virtual distributed patch area;
Determining a third distributed patch area with the shortest total task mileage in the second virtual distributed patch area;
Determining a fourth distributed patch area with the lowest total transportation cost in the third distributed patch area;
And determining the fourth distributed patch area as an optimal distributed patch area.
In some embodiments of the present application, the apparatus further includes a construction unit, configured to construct a location model of the distributed patch area before the optimizing each virtual distributed patch area in the set of virtual distributed patch areas to obtain an optimal distributed patch area;
The optimizing unit is specifically configured to: and optimizing the virtual distributed patch area by using the distributed patch area site selection model to obtain the optimal distributed patch area.
In another aspect, the present application also provides an electronic device, including:
One or more processors;
A memory; and
One or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the processor to implement the method of distributed point of flow indexing.
In another aspect, the present application also provides a computer readable storage medium having stored thereon a computer program, the computer program being loaded by a processor to perform the steps of the method for distributed point of sale location.
According to the embodiment of the invention, the logistics network information in the area to be planned is obtained, wherein the logistics network information comprises a lower logistics network point set, a candidate collection point set and a candidate bulk cargo point set in the area to be planned; generating a virtual distributed area set according to the logistics network information; and optimizing each virtual distribution area in the virtual distribution area set to obtain an optimal distribution area, wherein the optimal distribution area comprises at least one collection point and at least one bulk point. According to the embodiment of the invention, on the basis that the prior art collection and distribution point site selection has high limitation and the network node is required to have the functions of collecting and bulk cargo at the same time, the operation pressure of the collection and distribution point is reduced and the site selection efficiency of the collection and distribution point is improved by separating the collection and bulk cargo operation to different network nodes, so that the site selection result of the collection and distribution area is more comprehensive.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to fall within the scope of the invention.
In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. indicate orientations or positional relationships based on the drawings are merely for convenience in describing the present invention and simplifying the description, and do not indicate or imply that the apparatus or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more of the described features. In the description of the present invention, the meaning of "a plurality" is two or more, unless explicitly defined otherwise.
In the present application, the term "exemplary" is used to mean "serving as an example, instance, or illustration. Any embodiment described as "exemplary" in this disclosure is not necessarily to be construed as preferred or advantageous over other embodiments. The following description is presented to enable any person skilled in the art to make and use the application. In the following description, details are set forth for purposes of explanation. It will be apparent to one of ordinary skill in the art that the present application may be practiced without these specific details. In other instances, well-known structures and processes have not been described in detail so as not to obscure the description of the application with unnecessary detail. Thus, the present application is not intended to be limited to the embodiments shown, but is to be accorded the widest scope consistent with the principles and features disclosed herein.
The embodiment of the invention provides a method, a device, electronic equipment and a storage medium for selecting a physical distribution point. The following will describe in detail.
Referring to fig. 1, fig. 1 is a schematic view of a scenario of a logistics planning system according to an embodiment of the present invention, where the logistics planning system may include an electronic device 100, and a logistics distributed point location apparatus, such as the electronic device in fig. 1, is integrated in the electronic device 100.
In the embodiment of the present invention, the electronic device 100 is mainly used for obtaining logistics network information in an area to be planned, where the logistics network information includes a lower-level logistics network point set, a candidate collection point set and a candidate bulk cargo point set in the area to be planned; generating a virtual distributed area set according to the logistics network information; and optimizing each virtual distribution area in the virtual distribution area set to obtain an optimal distribution area, wherein the optimal distribution area comprises at least one collection point and at least one bulk point.
In the embodiment of the present invention, the electronic device 100 may be an independent server, or may be a server network or a server cluster formed by servers, for example, the electronic device 100 described in the embodiment of the present invention includes, but is not limited to, a computer, a network host, a single network server, a plurality of network server sets, or a cloud server formed by a plurality of servers. Wherein the Cloud server is composed of a large number of computers or web servers based on Cloud Computing (Cloud Computing).
It will be appreciated by those skilled in the art that the application environment shown in fig. 1 is merely an application scenario of the present application, and is not limited to the application scenario of the present application, and other application environments may also include more or fewer electronic devices than those shown in fig. 1, for example, only 1 electronic device is shown in fig. 1, and it will be appreciated that the logistics planning system may also include one or more other services, which are not limited herein.
In addition, as shown in fig. 1, the logistics planning system may further include a memory 200 for storing data, such as logistics data, for example, various data of a logistics platform, such as logistics transportation information of a transfer yard, logistics site information of each area, such as a transfer yard, lower logistics site information, and the like.
It should be noted that, the schematic view of the scenario of the logistics planning system shown in fig. 1 is only an example, and the logistics planning system and scenario described in the embodiments of the present invention are for more clearly describing the technical solution of the embodiments of the present invention, and do not constitute a limitation on the technical solution provided by the embodiments of the present invention, and those skilled in the art can know that, with the evolution of the logistics planning system and the appearance of a new service scenario, the technical solution provided by the embodiments of the present invention is equally applicable to similar technical problems.
Firstly, in the embodiment of the invention, a method for selecting a physical distribution point is provided, which comprises the following steps: acquiring logistics network information in an area to be planned, wherein the logistics network information comprises a lower logistics network point set, a candidate collection point set and a candidate bulk cargo point set in the area to be planned; generating a virtual distributed area set according to the logistics network information; and optimizing each virtual distribution area in the virtual distribution area set to obtain an optimal distribution area, wherein the optimal distribution area comprises at least one collection point and at least one bulk point.
Referring to fig. 2, a flow chart of an embodiment of a method for selecting a physical distribution point according to an embodiment of the present invention includes:
201. and acquiring logistics network information in the area to be planned.
The logistics network information comprises a lower logistics network point set, a candidate collection point set and a candidate bulk point set in the area to be planned. The area to be planned is a logistics dividing area, and may correspond to an administrative area, for example, a city B area, or may be a set area under a certain administrative area, which is not limited herein, and is only required to be an area where logistics distribution points are required to be selected.
The logistics network structure refers to a network structure composed of two basic elements, namely a line for executing logistics exercises and a node for executing logistics pause exercises. The logistics network can be divided into two parts of a line and a logistics network point, which are mutually interweaved and connected to form the logistics network.
The logistics network point is also called a logistics node and is a node for connecting logistics lines in a logistics network, so that the logistics network point is also called a logistics node. The types of the logistics nodes are various, and names of the nodes on different lines are different, and the logistics nodes are industrially called as distributed points and receiving points which are formed by the respective development influences of the fields of transportation, foreign trade, business and the like before the logistics discipline is formed.
The distribution points are the goods concentratedly, the goods are intensively processed and sorted at the place, the goods are classified, the place with the basic functions of logistics fully represented is realized, the basic logistics operation process of common goods distribution is realized, corresponding logistics infrastructure and equipment are needed, the logistics network realizes the centralized collection and distribution of the goods by selecting the distribution points, and the storage and transportation cost is reduced while the efficiency is improved. The logistics network points completing the functions are collection points, the logistics network points completing the bulk functions are bulk points, and the network points completing the collection functions and the bulk functions are collection and distribution points. The lower-level logistics network point can be a collection and distribution point, a collection and distribution point or a lower-level logistics network point corresponding to a bulk cargo point, for example, one collection and distribution point can correspond to a plurality of receiving and sending points (such as business points for receiving and sending express delivery), and the plurality of receiving and sending points are lower-level logistics network points of the collection and distribution point.
In some embodiments of the present invention, the logistics network information may include:
(1) Longitude and latitude information of candidate cargo collecting points, candidate bulk cargo points and subordinate logistics network points in the area to be planned;
(2) Travel time and mileage between all subordinate logistics network points in the area to be planned;
(3) In all subordinate logistics network points in the area to be planned, the aging requirement of the transportation task comprises the following steps: originating logistics website longitude and latitude, destination logistics website longitude and latitude, timestamp of earliest departure time and timestamp of latest arrival time;
(4) The number of lower-level logistics network points which can be borne by each pair of distributed points;
(5) The number of maximum distributed point pairs;
(6) The processing time of the goods at the distributed points comprises sorting time and loading and unloading time;
(7) The cost of a single kilometer of the vehicle;
(8) The maximum operation time of the distributed area addressing method.
202. And generating a virtual distributed area set according to the logistics network information.
Specifically, as shown in fig. 3, generating the virtual patch area set according to the logistics network information in step 202 may further include:
301. And generating a virtual distribution area set according to the candidate collection point set and the candidate bulk point set, wherein the collection points in the candidate collection point set and the bulk points in the candidate bulk point set belong to at least one virtual distribution area in the virtual distribution area set.
In an implementation, the generating a virtual distributed patch area set according to the candidate cargo point set and the candidate bulk cargo point set may include: sequentially selecting one collection point from the candidate collection point set, selecting one bulk point from the candidate bulk point set, and constructing collection and distribution point pairs; and generating a virtual distribution area for the distribution point pair until the collection points in the candidate collection point set and the bulk points in the candidate bulk point set belong to at least one virtual distribution area.
For example, a collection point i is selected from the candidate collection point set SC, a bulk point j is selected from the candidate bulk point set SD, a collection and distribution point pair Pij is constructed, and a virtual collection and distribution area aij is generated for Pij; repeating the above operation until both SC and SD belong to at least one virtual patch area, and generating a virtual patch area set.
302. And placing each lower-level logistics network point in the lower-level logistics network point set into a virtual distribution area of the virtual distribution area set, so that each lower-level logistics network point in the lower-level logistics network point set belongs to one virtual distribution area in the virtual distribution area set.
In a specific implementation, the placing each lower-level logistics dot in the lower-level logistics dot set into the virtual distribution area of the virtual distribution area set, so that each lower-level logistics dot in the lower-level logistics dot set belongs to one virtual distribution area in the virtual distribution area set, includes: randomly selecting a lower-level logistics network point from the lower-level logistics network point set in sequence, and randomly selecting a virtual distributed patch area from the virtual distributed patch area set; and placing the currently selected lower-level logistics network points into the currently selected virtual distributed patch area until each lower-level logistics network point in the lower-level logistics network point set belongs to one virtual distributed patch area in the virtual distributed patch area set.
For example, a lower-level logistics network point k is randomly selected from the lower-level logistics network point set SN, a virtual distribution area aij is randomly selected from the virtual distribution area set SA, and the lower-level logistics network point k is placed in the virtual distribution area aij (the lower-level logistics network point k is called as belonging to the virtual distribution area aij and simultaneously belonging to the collection point i and the bulk point j); the above operation is repeated until each of the subordinate logistics dots in SN belongs to a certain virtual distributed patch area.
203. And optimizing each virtual distribution area in the virtual distribution area set to obtain an optimal distribution area, wherein the optimal distribution area comprises at least one collection point and at least one bulk point.
According to the embodiment of the invention, the logistics network information in the area to be planned is obtained, wherein the logistics network information comprises a lower logistics network point set, a candidate collection point set and a candidate bulk cargo point set in the area to be planned; generating a virtual distributed area set according to the logistics network information; and optimizing each virtual distribution area in the virtual distribution area set to obtain an optimal distribution area, wherein the optimal distribution area comprises at least one collection point and at least one bulk point. According to the embodiment of the invention, on the basis that the prior art collection and distribution points have high site selection limitation and the network node is required to have the functions of collecting and bulk cargo at the same time, the operation pressure of the collection and distribution points is reduced and the site selection efficiency of the collection and distribution points is improved by separating the collection and bulk cargo operation to different network nodes, so that the site selection result is more comprehensive.
In some embodiments of the present invention, as shown in fig. 4, optimizing each virtual patch panel in the virtual patch panel set in step 203 to obtain an optimal patch panel may include:
401. And adjusting the attribution relation of the lower logistics network points of each virtual distributed area in the virtual distributed area set according to a preset constraint condition to obtain the virtual distributed area set after adjustment.
Wherein the constraint conditions may include the following:
(1) Maximum non-empty virtual distributed patch constraints: if at least one subordinate logistics network point exists in the virtual distributed area, the virtual distributed area is called as non-empty, and the number of the non-empty virtual distributed area cannot exceed the number of the maximum distributed point pairs designated in the logistics network information (5) in the step 201;
(2) And (5) size constraint of a non-empty virtual distributed area: the number of lower-level logistics network points in the virtual distributed area is called the scale of the virtual distributed area, and the scale of any virtual distributed area cannot exceed the number of lower-level logistics network points which can be borne by each pair of distributed points designated in the logistics network information (4) in the step 201;
(3) Cargo collection point uniqueness constraints: any goods collection point can only be simultaneously assigned to a non-empty virtual distributed area;
(4) Bulk point uniqueness constraints: any bulk cargo point can only be simultaneously assigned to a non-empty virtual collecting and distributing area;
(5) Lower logistics site uniqueness constraint: any subordinate logistics network point can only be simultaneously attributed to a non-empty virtual distributed area.
In the embodiment of the invention, in the optimization process, the specific mode of adjusting the virtual distributed area is to change the attribution relation of lower-level logistics network points in the virtual distributed area, and the specific adjusting method comprises the following steps:
(a) Unidirectional single-stream website movement: taking out a single lower logistics network point k from the original attribution virtual distributed patch area Aij, and attributing the single lower logistics network point k to a new virtual distributed patch area Ai′j′;
(b) Bidirectional single-stream website movement: taking out the lower-level logistics lattice point k in the virtual distributed area Aij and the lower-level logistics lattice point k 'in the virtual distributed area Ai′j′ simultaneously, and attributing k' to Aij and k to Ai′j′ simultaneously;
(c) Unidirectional multi-stream website movement: taking out a plurality of object flow downstream net points { k1,k2,...,kN } in the virtual distributed area Aij and attributing the net points to a new virtual distributed area Ai′j′, wherein N is not more than the scale of Aij;
(d) Bi-directional multi-stream dot movement: taking out a plurality of lower-level logistics network points { k1,k2,...,kN } in a virtual distributed patch area Aij, and taking out a plurality of lower-level logistics network points { k'1,k′2,...,k′M } in a virtual distributed patch area Ai′j′, wherein N is not greater than the scale of Aij, M is not greater than the scale of Ai′j′, and N and M can be unequal;
402. And respectively taking each virtual distributed area in the adjusted virtual distributed area set as a target virtual distributed area, and calculating the sum task programmable time length, the overtime task number, the sum task mileage and the sum transportation cost corresponding to the target distributed area.
The total task planning duration, the number of overtime tasks, the total task mileage and the total transportation cost corresponding to the target distributed area are calculated as follows:
(1) Sum task programmable duration: assuming that the originating node of a transport task T is k, the k belongs to the virtual distributed area Aij, the destination node is k ', the k' belongs to the virtual distributed area Ai′j′, the earliest departure time is Ts, the latest arrival time is Te, and the calculation mode of the programmable duration Tp of the task T is as shown in formula (1)
tp＝(te-ts)-(toc+t1+tcs+t2+tsd) (1)
In formula (1), toc is the travel time from the originating node k to the home pick-up node i;
t1 is the duration of the operation at the pick-up point i;
tcs is the travel time from the collection point i of the originating virtual collection and distribution area aij to the bulk point j' of the destination virtual collection and distribution area ai′j′;
t2 is the length of time of the operation at bulk point j';
tsd is the driving time from the bulk point j 'to the destination point k';
the sum of the programmable durations of all the transportation tasks is recorded as the sum of the programmable durations;
(2) Number of overtime tasks: if the programmable duration of a transport task is less than 0, the task is called a overtime task;
(3) Sum task mileage: similar to the definition of the programmable duration in (1), the mileage d of a transportation mission is calculated as shown in formula (2)
d＝doc+dcs+dsd (2)
In the formula (2), doc is the driving distance from the originating node k to the goods collection point i to which the originating node k belongs;
dcs is the driving distance from the collection point i of the originating virtual collection and distribution area aij to the bulk point j' of the destination virtual collection and distribution area ai′j′;
dsd is the driving distance from the bulk point j 'to the destination point k';
the sum of all the transportation mission mileage is recorded as the total mission mileage;
(4) Sum transport cost: the aggregate mission cost is equal to the aggregate mission mileage multiplied by the cost per kilometer of the vehicle specified in the logistics network information as described in step 201.
403. And optimizing each virtual distributed area in the virtual distributed area set according to the adjusted total task planning duration, the number of overtime tasks, the total task mileage and the total transportation cost corresponding to each virtual distributed area in the virtual distributed area set to obtain the optimal distributed area.
In a specific embodiment, as shown in fig. 5, the optimizing each virtual distribution area in the virtual distribution area set according to the adjusted sum task programmable duration, the number of overtime tasks, the sum task mileage and the sum transportation cost corresponding to each virtual distribution area in the virtual distribution area set to obtain an optimal distribution area includes:
501. and determining a first virtual distributed area with the minimum overtime task number in the overtime task number corresponding to each virtual distributed area in the adjusted virtual distributed area set.
502. And determining a second virtual distributed patch area with the longest sum programmable duration in the first virtual distributed patch area.
503. And determining a third distributed patch area with the shortest total mission mileage in the second virtual distributed patch area.
504. And determining a fourth distributed patch area with the lowest total transportation cost in the third distributed patch area.
505. And determining the fourth distributed patch area as an optimal distributed patch area.
In this embodiment, an optimal distributed area is determined according to the four indexes (1) to (4) calculated in step 402, wherein the overtime task number is a first-stage optimization target, the sum programmable duration is a second-stage optimization target, the sum task mileage is a third-stage optimization target, and the sum transportation cost is a fourth-stage optimization target; the method for selecting the physical distribution points in the embodiment of the invention optimizes the first-stage target first, optimizes the second-stage target on the basis that the first-stage optimization target cannot be further optimized, and the like; the overall goal of the method for selecting the physical distribution points is that the number of overtime tasks is the least, the total planable duration is the longest, the total task mileage is the shortest, and the total transportation cost is the lowest. According to the embodiment of the invention, the transportation aging and the transportation cost are comprehensively considered, and the evaluation of the logistics distributed point site selection result is more objective and comprehensive.
Further, after the attribution relation of the lower logistics network points is adjusted each time, whether the set of the optimal virtual distributed areas determined after adjustment is proper or not is determined according to the simulated annealing and short-time tabu strategies, at the moment, a heuristic algorithm is designed based on simulated annealing and tabu search, the method is suitable for the distributed point site selection problem of a large-scale network, and the operation efficiency and the solving quality are improved.
In the embodiment of the present invention, the optimization of each virtual distributed area in the virtual distributed area set may be performed using a preset distributed area site selection model, where the distributed area site selection model may be an integer programming model, input data of the integer programming model may be parameters in the logistics network information (1) to (8) in step 201, and an objective function of the integer programming model is a minimum timeout task number, a longest sum programmable duration, a shortest sum task mileage, and a minimum sum transportation cost; the constraints of the integer programming model may be the constraints in step 401.
The method for selecting the physical distribution points in the embodiment of the invention is described in detail by a specific embodiment, and is specifically as follows:
(1) Acquiring input information, specifically, logistics network information (1) to (8) described in step 201;
(2) Constructing an initial distributed patch area site selection scheme: a collection point i is selected from the candidate collection point set SC, a bulk point j is selected from the candidate bulk point set SD, a collection and distribution point pair Pij is constructed, and a virtual collection and distribution area Aij is generated for Pij; repeating the above operation until both SC and SD belong to at least one virtual distributed patch area; randomly selecting a lower-level logistics network point k from the lower-level logistics network point set SN, randomly selecting a virtual distribution area Aij from the virtual distribution area set SA, and placing the lower-level logistics network point k into the virtual distribution area Aij (at the moment, the lower-level logistics network point k is called as belonging to the virtual distribution area Aij and simultaneously belonging to a collection point i and a bulk point j); repeating the operation until each subordinate logistics network point in SN belongs to a certain virtual distributed area;
(3) Constructing constraint conditions of a distributed area site selection model (integer programming model), specifically, constraint conditions in step 401;
(4) And constructing a hierarchical optimization objective function of the distributed area site selection model, wherein the hierarchical optimization objective function comprises the minimum number of overtime tasks, the longest sum programmable duration, the shortest sum task mileage and the lowest sum transportation cost, and the calculation modes of the overtime task number, the sum programmable duration, the sum task mileage and the sum transportation cost are shown in the calculation processes of steps (1) - (4) in step 402, and are not repeated herein.
In the step, a hierarchical optimization objective function is constructed, wherein the overtime task number is a first-stage optimization objective, the sum programmable duration is a second-stage optimization objective, the sum task mileage is a third-stage optimization objective, and the sum transportation cost is a fourth-stage optimization objective; the method for selecting the address of the scheme comprises the steps of firstly optimizing a first-stage target, optimizing a second-stage target on the basis that the first-stage target cannot be further optimized, and the like; the overall goal of the address selection method in the embodiment is that the number of overtime tasks is minimum, the total planable duration is longest, the total task mileage is shortest, and the total transportation cost is lowest;
(5) And (3) adjusting a virtual distributed patch area: the specific method for adjusting the virtual distributed area is to change the attribution relation of the lower-level logistics network points in the virtual distributed area, and the specific adjusting method is as four ways from (a) to (d) in step 401.
Starting a TIMER from the current time; the initial addressing scheme is marked as S0; setting a most preferred address scheme Sopt＝S0, randomly selecting one of the four moving modes in the step 401 (a), (b), (c) and (d), and adjusting the virtual film area to obtain a temporary address scheme Stemp; performing constraint verification according to the constraint defined in step (3); calculating an optimization target value according to the optimization target defined in the step (4); determining whether to accept Stemp according to the simulated annealing and short-time tabu strategy, if so, Sopt＝Stemp, otherwise Sopt＝Sopt; if the TIMER duration is less than the model maximum run duration specified in S18, repeating steps S52-S55; otherwise, exiting the model calculation; outputting an optimal distributed area addressing scheme: and Sopt obtained in the step S5 is used as an optimal distributed area addressing scheme.
In order to better implement the method for selecting the site of the physical distribution point in the embodiment of the present invention, on the basis of the method for selecting the site of the physical distribution point, the embodiment of the present invention further provides a device for selecting the site of the physical distribution point, as shown in fig. 6, where the device for selecting the site of the physical distribution point includes an obtaining unit 601, a generating unit 602 and an optimizing unit 603, and specifically includes the following steps:
The obtaining unit 601 is configured to obtain logistics network information in an area to be planned, where the logistics network information includes a lower-level logistics dot set, a candidate collection dot set and a candidate bulk dot set in the area to be planned;
a generating unit 602, configured to generate a virtual distributed patch area set according to the logistics network information;
And the optimizing unit 603 is configured to optimize each virtual distribution area in the set of virtual distribution areas to obtain an optimal distribution area, where the optimal distribution area includes at least one cargo collection point and at least one bulk cargo point.
In some embodiments of the present application, the generating unit 602 is specifically configured to:
Generating a virtual distribution area set according to the candidate collection point set and the candidate bulk point set, wherein the collection points in the candidate collection point set and the bulk points in the candidate bulk point set belong to at least one virtual distribution area in the virtual distribution area set;
And placing each lower-level logistics network point in the lower-level logistics network point set into a virtual distribution area of the virtual distribution area set, so that each lower-level logistics network point in the lower-level logistics network point set belongs to one virtual distribution area in the virtual distribution area set.
In some embodiments of the present application, the generating unit 602 is specifically configured to:
sequentially selecting one collection point from the candidate collection point set, selecting one bulk point from the candidate bulk point set, and constructing collection and distribution point pairs;
And generating a virtual distribution area for the distribution point pair until the collection points in the candidate collection point set and the bulk points in the candidate bulk point set belong to at least one virtual distribution area.
In some embodiments of the present application, the generating unit 602 is specifically configured to:
Randomly selecting a lower-level logistics network point from the lower-level logistics network point set in sequence, and randomly selecting a virtual distributed patch area from the virtual distributed patch area set;
And placing the currently selected lower-level logistics network points into the currently selected virtual distributed patch area until each lower-level logistics network point in the lower-level logistics network point set belongs to one virtual distributed patch area in the virtual distributed patch area set.
In some embodiments of the present application, the optimizing unit 603 is specifically configured to:
the attribution relation of the lower logistics network points of each virtual distributed area in the virtual distributed area set is adjusted according to preset constraint conditions, and the virtual distributed area set after adjustment is obtained;
Respectively taking each virtual distributed area in the adjusted virtual distributed area set as a target virtual distributed area, and calculating the sum task programmable time length, the overtime task number, the sum task mileage and the sum transportation cost corresponding to the target distributed area;
And optimizing each virtual distributed area in the virtual distributed area set according to the adjusted total task planning duration, the number of overtime tasks, the total task mileage and the total transportation cost corresponding to each virtual distributed area in the virtual distributed area set to obtain the optimal distributed area.
In some embodiments of the present application, the optimizing unit 603 is specifically configured to:
Determining a first virtual distributed area with the minimum overtime task number in the overtime task number corresponding to each virtual distributed area in the virtual distributed area set;
Determining a first virtual distributed area with the minimum overtime task number in the overtime task number corresponding to each virtual distributed area in the adjusted virtual distributed area set;
determining a second virtual distributed patch area with the longest sum of the programmable durations in the first virtual distributed patch area;
Determining a third distributed patch area with the shortest total task mileage in the second virtual distributed patch area;
Determining a fourth distributed patch area with the lowest total transportation cost in the third distributed patch area;
And determining the fourth distributed patch area as an optimal distributed patch area.
In some embodiments of the present application, the apparatus further includes a construction unit, configured to construct a location model of the distributed patch area before the optimizing each virtual distributed patch area in the set of virtual distributed patch areas to obtain an optimal distributed patch area;
The optimizing unit 603 is specifically configured to: and optimizing the virtual distributed patch area by using the distributed patch area site selection model to obtain the optimal distributed patch area.
In the embodiment of the invention, the logistics network information in the area to be planned is acquired through the acquisition unit 601, wherein the logistics network information comprises a lower logistics network point set, a candidate collection point set and a candidate bulk point set in the area to be planned; generating unit 602 generates a virtual distributed patch area set according to the logistics network information; the optimizing unit 603 optimizes each virtual distribution area in the virtual distribution area set to obtain an optimal distribution area, where the optimal distribution area includes at least one collection point and at least one bulk point. According to the embodiment of the invention, on the basis that the prior art collection and distribution points have high site selection limitation and the network node is required to have the functions of collecting and bulk cargo at the same time, the operation pressure of the collection and distribution points is reduced and the site selection efficiency of the collection and distribution points is improved by separating the collection and bulk cargo operation to different network nodes, so that the site selection result is more comprehensive.
The embodiment of the invention also provides electronic equipment, which integrates any one of the logistics distributed point location devices provided by the embodiment of the invention, and the electronic equipment comprises:
One or more processors;
A memory; and
One or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the processor to perform the steps of the method for physical distribution point location described in any of the embodiments of the method for physical distribution point location described above.
The embodiment of the invention also provides electronic equipment which integrates any one of the logistics distributed point location device provided by the embodiment of the invention. As shown in fig. 7, a schematic structural diagram of an electronic device according to an embodiment of the present invention is shown, specifically:
The electronic device may include one or more processing cores 'processors 701, one or more computer-readable storage media's memory 702, power supply 703, and input unit 704, among other components. It will be appreciated by those skilled in the art that the electronic device structure shown in fig. 7 is not limiting of the electronic device and may include more or fewer components than shown, or may combine certain components, or a different arrangement of components.
Wherein:
The processor 701 is a control center of the electronic device, connects various parts of the entire electronic device using various interfaces and lines, and performs various functions of the electronic device and processes data by running or executing software programs and/or modules stored in the memory 702, and calling data stored in the memory 702, thereby performing overall monitoring of the electronic device. Optionally, processor 701 may include one or more processing cores; preferably, the processor 701 may integrate an application processor and a modem processor, wherein the application processor primarily handles operating systems, user interfaces, applications, etc., and the modem processor primarily handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 701.
The memory 702 may be used to store software programs and modules, and the processor 701 executes various functional applications and data processing by executing the software programs and modules stored in the memory 702. The memory 702 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program (such as a sound playing function, an image playing function, etc.) required for at least one function, and the like; the storage data area may store data created according to the use of the electronic device, etc. In addition, the memory 702 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, the memory 702 may also include a memory controller to provide access to the memory 702 by the processor 701.
The electronic device further comprises a power supply 703 for powering the various components, preferably the power supply 703 is logically connected to the processor 701 by a power management system, whereby the functions of managing charging, discharging, and power consumption are performed by the power management system. The power supply 703 may also include one or more of any component, such as a direct current or alternating current power supply, a recharging system, a power failure detection circuit, a power converter or inverter, a power status indicator, etc.
The electronic device may further comprise an input unit 704, which input unit 704 may be used for receiving input digital or character information and generating keyboard, mouse, joystick, optical or trackball signal inputs in connection with user settings and function control.
Although not shown, the electronic device may further include a display unit or the like, which is not described herein. In particular, in this embodiment, the processor 701 in the electronic device loads executable files corresponding to the processes of one or more application programs into the memory 702 according to the following instructions, and the processor 701 executes the application programs stored in the memory 702, so as to implement various functions as follows:
acquiring logistics network information in an area to be planned, wherein the logistics network information comprises a lower logistics network point set, a candidate collection point set and a candidate bulk cargo point set in the area to be planned; generating a virtual distributed area set according to the logistics network information; and optimizing each virtual distribution area in the virtual distribution area set to obtain an optimal distribution area, wherein the optimal distribution area comprises at least one collection point and at least one bulk point.
Those of ordinary skill in the art will appreciate that all or a portion of the steps of the various methods of the above embodiments may be performed by instructions, or by instructions controlling associated hardware, which may be stored in a computer-readable storage medium and loaded and executed by a processor.
To this end, an embodiment of the present invention provides a computer-readable storage medium, which may include: read Only Memory (ROM), random access Memory (RAM, random Access Memory), magnetic or optical disk, and the like. The method comprises the steps of storing a computer program, wherein the computer program is loaded by a processor to execute the steps in any one of the logistics distributed point and site selection methods provided by the embodiment of the invention. For example, the loading of the computer program by the processor may perform the steps of:
acquiring logistics network information in an area to be planned, wherein the logistics network information comprises a lower logistics network point set, a candidate collection point set and a candidate bulk cargo point set in the area to be planned; generating a virtual distributed area set according to the logistics network information; and optimizing each virtual distribution area in the virtual distribution area set to obtain an optimal distribution area, wherein the optimal distribution area comprises at least one collection point and at least one bulk point.
In the foregoing embodiments, the descriptions of the embodiments are focused on, and the portions of one embodiment that are not described in detail in the foregoing embodiments may be referred to in the foregoing detailed description of other embodiments, which are not described herein again.
In the implementation, each unit or structure may be implemented as an independent entity, or may be implemented as the same entity or several entities in any combination, and the implementation of each unit or structure may be referred to the foregoing method embodiments and will not be repeated herein.
The specific implementation of each operation above may be referred to the previous embodiments, and will not be described herein.
The above describes in detail a method, a device, an electronic device and a storage medium for selecting a physical distribution point provided by the embodiment of the present invention, and specific examples are applied to describe the principle and implementation of the present invention, where the description of the above embodiment is only used to help understand the method and core idea of the present invention; meanwhile, as those skilled in the art will have variations in the specific embodiments and application scope in light of the ideas of the present invention, the present description should not be construed as limiting the present invention.