用mathematica写一个，求解商旅问题的程序

以下是用Mathematica编写的商旅问题求解程序，基于遗传算法：

(*定义城市数量*)

cityNum = 10;

(*定义城市坐标*)

cityPos = RandomReal[{-10, 10}, {cityNum, 2}];

(*定义初始种群数量*)

popNum = 100;

(*定义遗传算法参数*)

generationNum = 100;

mutationProb = 0.1;

crossoverProb = 0.8;

(*定义目标函数：计算旅行代价*)

travelCost[route_] := Total[EuclideanDistance @@@ Partition[cityPos[[route]], 2, 1, 1]];

(*定义交叉函数：将两个个体进行交叉操作*)

crossover[parent1_, parent2_] := Module[{pos, child1, child2},

pos = RandomInteger[{1, cityNum - 1}];

child1 = Join[parent1[[1 ;; pos]], Complement[parent2, parent1[[1 ;; pos]]]];

child2 = Join[parent2[[1 ;; pos]], Complement[parent1, parent2[[1 ;; pos]]]];

{child1, child2}

];

(*定义变异函数：随机交换两个城市的位置*)

mutation[individual_] := Module[{pos1, pos2},

{pos1, pos2} = RandomSample[Range[cityNum], 2];

ReplacePart[individual, {pos1 -> individual[[pos2]], pos2 -> individual[[pos1]]}]

];

(*定义选择函数：根据旅行代价排序，选择前一半个体*)

selection[population_] := SortBy[population, travelCost][[1 ;; popNum/2]];

(*定义初始化种群*)

initialPopulation = Table[RandomSample[Range[cityNum]], popNum];

(*定义主程序*)

result = Nest[Module[{parents, offspring},

parents = RandomSample[selection[#], 2];

If[RandomReal[] < crossoverProb,

offspring = crossover @@ parents,

offspring = parents;

];

offspring = If[RandomReal[] < mutationProb,

mutation /@ offspring,

offspring

];

Join[#, offspring]

] &, initialPopulation, generationNum];

bestRoute = SortBy[result, travelCost][[1]];

bestCost = travelCost[bestRoute];

(*输出结果*)

Print["最优路径：", bestRoute];

Print["最优代价：", bestCost];

ListLinePlot[Append[cityPos[[bestRoute]], First[cityPos[[bestRoute]]]],

PlotStyle -> {Red, PointSize[Large]},

AspectRatio -> Automatic,

ImageSize -> 500,

Axes -> False,

Frame -> True,

FrameTicks -> None,

Background -> Black,

Epilog -> {White, Text[Style["Traveling Salesman Problem", 20, Bold], Scaled[{0.5, 0.95}]]}

]

]