Features

Install

<dependency>  <groupId>com.github.chen0040</groupId>  <artifactId>java-swarm-intelligence</artifactId>  <version>1.0.5</version></dependency>

Usage

Bees Swarm

CostFunctionRosenbrock =newCostFunction() {publicdoublecalc(doublex,doubley) {doubleexpr1 = (x*x -y);doubleexpr2 =1 -x;return100 *expr1*expr1 +expr2*expr2; }@Overridepublicdoubleevaluate(List<Double>solution,List<Double>lowerBounds,List<Double>upperBounds) {returncalc(solution.get(0),solution.get(1)); }};BeeSwarmswarm =newBeeSwarm();swarm.setUpperBounds(Arrays.asList(5.0,5.0));swarm.setLowerBounds(Arrays.asList(-5.0, -5.0));swarm.setDimension(2);swarm.setCostFunction(Rosenbrock);swarm.setMaxIterations(50);BeebestSolution =swarm.solve();logger.info("best solution: {} cost: {}",bestSolution,bestSolution.getCost());List<Double>trend =swarm.getCostTrend();logger.info("trend: {}",trend);

CostTrendchart =newCostTrend(trend,"Cost vs Generation");chart.showIt(true);

Particle Swarm Optimization

CostFunctionRosenbrock =newCostFunction() {publicdoublecalc(doublex,doubley) {doubleexpr1 = (x*x -y);doubleexpr2 =1 -x;return100 *expr1*expr1 +expr2*expr2; }@Overridepublicdoubleevaluate(List<Double>solution,List<Double>lowerBounds,List<Double>upperBounds) {returncalc(solution.get(0),solution.get(1)); }};ParticleSwarmswarm =newParticleSwarm();swarm.setUpperBounds(Arrays.asList(5.0,5.0));swarm.setLowerBounds(Arrays.asList(-5.0, -5.0));swarm.setDimension(2);swarm.setCostFunction(Rosenbrock);swarm.setMaxIterations(50);ParticlebestSolution =swarm.solve();logger.info("best solution: {} cost: {}",bestSolution,bestSolution.getCost());List<Double>trend =swarm.getCostTrend();logger.info("trend: {}",trend);

CostTrendchart =newCostTrend(trend,"Cost vs Generation");chart.showIt(true);

Ant System

// load the bayg29 TSP instanceTspBenchmarkbenchmark =Tsp.get(Tsp.Instance.bayg29);PathCostFunctioncostFunction =newPathCostFunction() {// compute the cost of the tour constructed by an ant on the problem bayg29@Overridepublicdoubleevaluate(List<Integer>path) {doublecost =0;for(inti=0;i <path.size(); ++i) {intj = (i+1) %path.size();doubledistance =benchmark.distance(path.get(i),path.get(j));cost +=distance;    }returncost; }// heuristic weight for transition from state1 to state2 during path construction// the higher the weight the more favorable to transit from state1 to state2@OverridepublicdoublestateTransitionWeight(intstate1,intstate2) {return1 / (1 +benchmark.distance(state1,state2)); }};AntSystemantSystem =newAntSystem();antSystem.setProblemSize(benchmark.size());antSystem.setCostFunction(costFunction);antSystem.setMaxIterations(100);AntbestAnt =antSystem.solve();System.out.println("minimal total distance found by Ant System: " +bestAnt.getCost());System.out.println("known minimal total distance: " +costFunction.evaluate(benchmark.optTour()));System.out.println("best TSP path found: ");for(inti=0;i <bestAnt.getPath().size(); ++i) {intj = (i +1) %bestAnt.getPath().size();System.out.println(bestAnt.getPath().get(i) +" => " +bestAnt.getPath().get(j));}

CostTrendchart =newCostTrend(antSystem.getCostTrend(),"Cost vs Generation");chart.showIt(true);

Ant Colony System

TspBenchmarkbenchmark =Tsp.get(Tsp.Instance.bayg29);PathCostFunctioncostFunction =newPathCostFunction() {@Overridepublicdoubleevaluate(List<Integer>path) {doublecost =0;for(inti=0;i <path.size(); ++i) {intj = (i+1) %path.size();doubledistance =benchmark.distance(path.get(i),path.get(j));cost +=distance;     }returncost;  }// heuristic weight for transition from state1 to state2 during path construction// the higher the weight the more favorable to transit from state1 to state2@OverridepublicdoublestateTransitionWeight(intstate1,intstate2) {return1 / (1 +benchmark.distance(state1,state2));  }};AntColonySystemantColonySystem =newAntColonySystem();antColonySystem.setProblemSize(benchmark.size());antColonySystem.setCostFunction(costFunction);antColonySystem.setMaxIterations(100);AntbestAnt =antColonySystem.solve();System.out.println("minimal total distance found: " +bestAnt.getCost());System.out.println("best known cost: " +costFunction.evaluate(benchmark.optTour()));System.out.println("best path found: ");for(inti=0;i <bestAnt.getPath().size(); ++i) {intj = (i +1) %bestAnt.getPath().size();System.out.println(bestAnt.getPath().get(i) +" => " +bestAnt.getPath().get(j));}

CostTrendchart =newCostTrend(antColonySystem.getCostTrend(),"Cost vs Generation");chart.showIt(true);