Ingeometry, theWeber problem, named afterAlfred Weber, is one of the most famous problems inlocation theory. It requires finding a point in the plane that minimizes the sum of the transportation costs from this point ton destination points, where different destination points are associated with different costs per unit distance.

The Weber problem generalizes thegeometric median, which assumes transportation costs per unit distance are the same for all destination points, and the problem of computing theFermat point, the geometric median of three points. For this reason it is sometimes called the Fermat–Weber problem, although the same name has also been used for the unweighted geometric median problem. The Weber problem is in turn generalized by theattraction–repulsion problem, which allows some of the costs to be negative, so that greater distance from some points is better.

In the triangle case, the Fermat problem consists in locating a pointD with respect to three pointsA, B, C in such a way that the sum of the distances betweenD and each of the three other points is minimized. It was formulated by the famous French mathematicianPierre de Fermat before 1640, and it can be seen as the true beginning of both location theory, and space-economy. Torricelli found a geometrical solution to this problem around 1645, but it still had no direct numerical solution more than 325 years later. E. Weiszfeld published a paper in 1937 with an algorithm for the Fermat-Weber problem. As the paper was published in Tohoku Mathematical journal, and Weiszfeld immigrated to USA and changed his name to Vaszoni, his work was not widely known.^[1] Kuhn and Kuenne^[2] independently found a similar iterative solution for the general Fermat problem in 1962, and, in 1972,Tellier^[3] found a direct numerical solution to the Fermat triangle problem, which is trigonometric. Kuhn and Kuenne's solution applies to the case of polygons having more than three sides, which is not the case with Tellier's solution for reasons explained further on.

The Weber problem consists, in the triangle case, in locating a pointD with respect to three pointsA, B, C in such a way that the sum of the transportation costs betweenD and each of the three other points is minimized. The Weber problem is a generalization of the Fermat problem since it involves both equal and unequal attractive forces (see below), while the Fermat problem only deals with equal attractive forces. It was first formulated, and solved geometrically in the triangle case, byThomas Simpson in 1750.^[4] It was later popularized byAlfred Weber in 1909.^[5] Kuhn and Kuenne's iterative solution found in 1962, and Tellier's solution found in 1972 apply to the Weber triangle problem as well as to the Fermat one. Kuhn and Kuenne's solution applies also to the case of polygons having more than three sides.

In its simplest version, the attraction-repulsion problem consists in locating a pointD with respect to three pointsA₁,A₂ andR in such a way that the attractive forces exerted by pointsA₁,A₂, and the repulsive force exerted by pointR cancel each other out as it must do at the optimum. It constitutes a generalization of both the Fermat and Weber problems. It was first formulated and solved, in the triangle case, in 1985 byLuc-Normand Tellier.^[6] In 1992, Chen, Hansen, Jaumard and Tuy found a solution to the Tellier problem for the case of polygons having more than three sides.

Evangelista Torricelli’s geometrical solution of the Fermat triangle problem stems from two observations:

1. PointD is at its optimal location when any significant move out of that location induces a net increase of the total distance to reference pointsA, B, C, which means that the optimal point is the only point where an infinitesimal movement towards one of the three reference points induces a reduction of the distance to that point that is equal to the sum of the induced changes in the distances to the two other points; in fact, in the Fermat problem, the advantage to reduce the distance fromA by one kilometer is equal to the advantage to reduce the distance fromB by one kilometer or the distance fromC by the same length; in other words, the activity to be located atD is equally attracted byA, B, C;
2. According to an important theorem of Euclidean geometry, in a convex quadrilateral inscribed in a circle, the opposite angles are supplementary (that is their sum is equal to 180°); that theorem can also take the following form: if we cut a circle with a chordAB, we get two circle arcs, let us sayAiB,AjB; on arcAiB, any∠AiB angle is the same for any chosen pointi, and, on arcAjB, all the∠AjB angles are also equal for any chosen pointj; moreover, the∠AiB, ∠AjB angles are supplementary.

It can be proved that the first observation implies that, at the optimum, the angles between theAD, BD, CD straight lines must be equal to 360° / 3 = 120°. Torricelli deduced from that conclusion that:

1. If any triangle△ABD, whose∠ADB angle is equal to 120°, generates anABDE convex quadrilateral inscribed in a circle, the∠ABE angle of the△ABE triangle must be equal to (180° − 120°) = 60°;
2. One way to determine the set of locations ofD for which the∠ADB angle is equal to 120° is to draw an equilateral△ABE triangle (because each angle of an equilateral triangle is equal to 60°), whereE is located outside the△ABC triangle, and draw a circle round that triangle; then all theD' points of the circumference of that circle that lie within the△ABC circle are such that the∠AD'B angle is equal to 120°;
3. The same reasoning can be made with respect to triangles△ACD, △BCD;
4. This leads to draw two other equilateral triangles△ACF, △BCG, whereF, G are located outside the△ABC triangle, as well as two other circles round these equilateral triangles, and to determine the location where the three circles intersect; at that location, the angles between theAD, BD, CD straight lines is necessarily equal to 120°, which proves that it is the optimal location.

Simpson's geometrical solution of the so-called "Weber triangle problem" (which was first formulated byThomas Simpson in 1750) directly derives from Torricelli's solution. Simpson and Weber stressed the fact that, in a total transportation minimization problem, the advantage to get closer to each attraction pointA, B orC depends on what is carried and on its transportation cost. Consequently, the advantage of getting one kilometer closer toA, B orC varies, and the∠ADB, ∠ADC, ∠BDC angles no more need to be equal to 120°.

Simpson demonstrated that, in the same way as, in the Fermat triangle problem case, the constructed triangles△ABE, △ACF, △BCG were equilateral because the three attractive forces were equal, in the Weber triangle problem case, the constructed triangles△ABE, △ACF, △BCG, whereE, F, G are located outside the△ABC triangle, must be proportional to the attractive forces of the location system.

The solution is such that:

1. In the constructed triangle△ABE, theAB side is proportional to the attractive forcew_C pointing towardsC, theAE side is proportional to the attractive forcew_B pointing towardsB, and theBE side is proportional to the attractive forcew_A pointing towardsA;
2. In the constructed triangle△BCG, theBC side is proportional to the attractive forcew_A pointing towardsA, theBG side is proportional to the attractive forcew_C pointing towardsB, and theCG side is proportional to the attractive forcew_B pointing towardsC;
3. The optimal pointD is located at the intersection of the two circumferences drawn round the△ABE, △BCG constructed triangles.

A third triangle of forces△ACF, whereF is located outside the△ABC triangle, can be drawn based on theAC side, and a third circumference can be traced round that triangle. That third circumference crosses the two previous ones at the same pointD.

A geometrical solution exists for the attraction-repulsion triangle problem. Its discovery is rather recent.^[7] That geometrical solution differs from the two previous ones since, in this case, the two constructed force triangles overlap the△A₁A₂R location triangle (whereA₁ andA₂ are attraction points, andR, a repulsion one), while, in the preceding cases, they never did.

This solution is such that:

1. In the constructed triangle△RA₂H, which partly overlaps the△A₁A₂R location triangle, theRA₂ side is proportional to the attractive forcew_A1 pointing towardsA₁, theRH side is proportional to the attractive forcew_A2 pointing towardsA₂, and theA₂H side is proportional to the repulsive forcew_R pushing away from pointR;
2. In the constructed triangle△RA₁I, which partly overlaps the△A₁A₂R location triangle, theRA₁ side is proportional to the attractive forcew_A2 pointing towardsA₂, theRI side is proportional to the attractive forcew_A1 pointing towardsA₁, and theA₁I side is proportional to the repulsive forcew_R pushing away from pointR;
3. The optimal pointD is located at the intersection of the two circumferences drawn round the△RA₂H and△RA₁I constructed triangles.

This solution is useless if one of the forces is greater than the sum of the two other ones or if the angles are not compatible. In some cases, no force is larger than the two other ones, and the angles are not compatible; then, the optimal location lies at the point that exerts the greater attractive force.

More than 332 years separate the first formulation of the Fermat triangle problem and the discovery of its non-iterative numerical solution, while a geometrical solution existed for almost all that period of time. Is there an explanation for that? That explanation lies in the possibility of the origins of the three vectors oriented towards the three attraction points not coinciding. If those origins do coincide and lie at the optimum locationP, the vectors oriented towardsA, B, C, and the sides of the△ABC location triangle form the six angles∠1, ∠2, ∠3, ∠4, ∠5, ∠6, and the three vectors form the∠α_A, ∠α_B, ∠α_C angles. It is easy to write the following six equations linking six unknowns (the angles∠1, ∠2, ∠3, ∠4, ∠5, ∠6) with six known values (angles∠A, ∠B, ∠C, whose values are given, and angles∠α_A, ∠α_B, ∠α_C, whose values depend only on the relative magnitude of the three attractive forces pointing towards theA, B, C attraction points):

Unfortunately, this system of six simultaneous equations with six unknowns is undetermined, and the possibility of the origins of the three vectors oriented towards the three attraction points not coinciding explains why. In the case of non-coincidence, we observe that all the six equations are still valid. However, the optimal locationP has disappeared because of the triangular hole that exists inside the triangle. In fact, as Tellier (1972)^[8] has shown, that triangular hole had exactly the same proportions as the "forces triangles" we drew in Simpson's geometrical solution.

In order to solve the problem, we must add to the six simultaneous equations a seventh requirement, which states that there should be no triangular hole in the middle of the location triangle. In other words, the origins of the three vectors must coincide.

Tellier's solution of the Fermat and Weber triangle problems involves three steps:

1. Determine the angles∠α_A, ∠α_B, ∠α_C that are such that the three attractive forcesw_A, w_B, w_C cancel each other to ensure equilibrium. This is done by means of the following independent equations:$${\displaystyle \begin{array}{r}\cos \mathrm{\angle }{\alpha }_A=-\frac{w_B^2+w_C^2-w_A^2}{2w_B{w}_C};\\ \cos \mathrm{\angle }{\alpha }_B=-\frac{w_A^2+w_C^2-w_B^2}{2w_A{w}_C};\\ \cos \mathrm{\angle }{\alpha }_C=-\frac{w_A^2+w_B^2-w_C^2}{2w_A{w}_B};\end{array}}$$
2. Determine the value of angle∠3 (this equation derives from the requirement that pointD must coincide with pointE):$${\displaystyle \tan \mathrm{\angle }3=\frac{k\sin k^{\prime }}{1+k\cos k^{\prime }};}$$ where
3. Solve the following system of simultaneous equations where∠3 is now known:

Tellier (1985)^[9] extended the Fermat–Weber problem to the case of repulsive forces. Let us examine the triangle case where there are two attractive forcesw_A1,w_A2, and one repulsive forcew_R. Here as in the previous case, the possibility exists for the origins of the three vectors not to coincide. So the solution must require their coinciding. Tellier's trigonometric solution of this problem is the following:

1. Determine angle∠e:$${\displaystyle \cos \mathrm{\angle }e=-\frac{w_{A1}^2+w_{A2}^2-w_R^2}{2w_{A1}{w}_{A2}};}$$
2. Determine angle∠p:$${\displaystyle \cos \mathrm{\angle }p=-\frac{w_{A1}^2+w_R^2-w_{A2}^2}{2w_{A1}{w}_R};}$$
3. Determine angle∠c:$${\displaystyle \mathrm{\angle }c={180}^{\circ }-\mathrm{\angle }p;}$$
4. Determine angle∠d:$${\displaystyle \mathrm{\angle }d=\mathrm{\angle }e-\mathrm{\angle }c;}$$
5. Determine the value of angle∠3 (this equation derives from the requirement that pointD must coincide with pointE):$${\displaystyle \tan \mathrm{\angle }3=\frac{x}{y};}$$ where
6. Determine∠1:$${\displaystyle \mathrm{\angle }1={180}^{\circ }-\mathrm{\angle }e-\mathrm{\angle }3;}$$
7. Determine∠5:$${\displaystyle \mathrm{\angle }5={180}^{\circ }-\mathrm{\angle }b-\mathrm{\angle }c-\mathrm{\angle }1;}$$
8. Determine∠2:$${\displaystyle \mathrm{\angle }2=\mathrm{\angle }a-\mathrm{\angle }5.}$$

When the number of forces is larger than three, it is no longer possible to determine the angles separating the various forces without taking into account the geometry of the location polygon. Geometric and trigonometric methods are then powerless. Iterative optimizing methods are used in such cases. Kuhn and Kuenne (1962)^[10] suggested an algorithm based oniteratively reweighted least squares generalizingWeiszfeld's algorithm for theunweighted problem. Their method is valid for the Fermat and Weber problems involving many forces, but not for the attraction–repulsion problem. In this method, to find an approximation to the pointy minimizing the weighted sum of distances$${\displaystyle \sum _{i=1}^n{w}_i\Vert x_i-y\Vert ,}$$an initial approximation to the solutiony₀ is found, and then at each stage of the algorithm is moved closer to the optimal solution by settingy_{j + 1} to be the point minimizing the sum of weighted squared distances$${\displaystyle \sum _{i=1}^n\frac{w_i}{\Vert x_i-y_j\Vert }\Vert x_i-y{\Vert }^2}$$where the initial weightsw_i of the input points are divided by the distances from each point to the approximation from the previous stage.As the unique optimal solution to a weighted least squares problem, each successive approximation may be found as a weighted average:$${\displaystyle y_{j+1}=\frac{{\displaystyle \sum _{i=1}^n\frac{w_i{x}_i}{|x_i-y_j|}}}{{\displaystyle \sum _{i=1}^n\frac{w_i}{|x_i-y_j|}}}}$$

TheVarignon frame provides an experimental solution of the Weber problem.

For the attraction–repulsion problem one has instead to resort to the algorithm proposed by Chen, Hansen, Jaumard and Tuy (1992).^[11]

In the world ofspatial economics, repulsive forces are omnipresent. Land values are the main illustration of them. In fact a substantial portion ofland value theory, both rural and urban, can be summed up in the following way.

In the case where everybody is attracted by a single attraction point (the rural market or the urban central business district), competition between the various bidders who all want to locate at the center will generate land values that will transform the unique attraction point of the system into a repulsion point from the land value point of view, and, at the equilibrium, each inhabitant and activity will be located at the point where the attractive and the repulsive forces exerted by the center on them will cancel out.

The Tellier problem preceded the emergence of theNew Economic Geography. It is seen by Ottaviano and Thisse (2005)^[12] as a prelude to the New Economic Geography (NEG) that developed in the 1990s, and earnedPaul Krugman aNobel Memorial Prize in Economic Sciences in 2008. The concept of attractive force is akin to the NEG concept of agglomeration or centripetal force, and the concept of repulsive force is akin to the NEG concept of dispersal or centrifugal force.

• Chen, Pey-Chun, Hansen, Pierre,Jaumard, Brigitte and Hoang Tuy, 1992, "Weber's Problem with Attraction and Repulsion,"Journal of Regional Science 32, 467–486.
• Kuhn, Harold W. and Robert E. Kuenne, 1962, "An Efficient Algorithm for the Numerical Solution of the Generalized Weber Problem in Spatial Economics."Journal of Regional Science 4, 21–34.
• Ottaviano, Gianmarco and Jacques-François Thisse, 2005, « New Economic Geography: what about the N? »,Environment and Planning A 37, 1707–1725.
• Simpson, Thomas, 1750, The Doctrine and Application of Fluxions, London.
• Tellier, Luc-Normand and Boris Polanski, 1989, "The Weber Problem: Frequency of Different Solution Types and Extension to Repulsive Forces and Dynamic Processes",Journal of Regional Science, vol 29, no. 3, p. 387–405.
• Tellier, Luc-Normand, 1972, "The Weber Problem: Solution and Interpretation",Geographical Analysis, vol. 4, no. 3, pp. 215–233.
• Tellier, Luc-Normand, 1985,Économie spatiale: rationalité économique de l'espace habité, Chicoutimi, Gaëtan Morin éditeur, 280 pages.
• Tellier, Luc-Normand, 2013, « Annexe 1: Solution géométrique du cas triangulaire du problème d’attraction–répulsion », annex of the paper of Pierre Hansen, Christophe Meyer and Luc-Normand Tellier, « Modèles topodynamique et de la Nouvelle économie géographique : compatibilité, convergence et avantages comparés », in Marc-Urbain Proulx (ed.), 2013,Sciences du territoire II : méthodologies, Québec, Presses de l’Université du Québec.
• Weber, Alfred, 1909,Über den Standort der Industrien, Tübingen, J.C.B. Mohr) — English translation:The Theory of the Location of Industries, Chicago, Chicago University Press, 1929, 256 pages.
• Wesolowski, Georges, 1993, «The Weber problem: History and perspective»,Location Science, Vol. 1, p. 5–23.

• "Weber problem",Encyclopedia of Mathematics,EMS Press, 2001 [1994]

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