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多旅行商matlab实验源码实现了三种多旅行商问题 % MTSPOF_GA Fixed Open Multiple Traveling Salesmen Problem (M-TSP) Genetic Algorithm (GA) % Finds a (near) optimal solution to a variation of the "open" M-TSP by % setting up a GA to search for the shortest route (least distance needed % for each salesman to travel from the start location to unique % individual cities and finally to the end location) % % Summary: % 1. Each salesman starts at the first point, and ends at the last % point, but travels to a unique set of cities in between (none of % them close their loops by returning to their starting points) % 2. Except for the first and last, each city is visited by exactly one salesman % % Note: The Fixed Start is taken to be the first XY point and the Fixed End % is taken to be the last XY point % % Input: % XY (float) is an Nx2 matrix of city locations, where N is the number of cities % DMAT (float) is an NxN matrix of city-to-city distances or costs % SALESMEN (scalar integer) is the number of salesmen to visit the cities % MIN_TOUR (scalar integer) is the minimum tour length for any of the % salesmen, NOT including the start point or end point % POP_SIZE (scalar integer) is the size of the population (should be divisible by 8) % NUM_ITER (scalar integer) is the number of desired iterations for the algorithm to run % SHOW_PROG (scalar logical) shows the GA progress if true % SHOW_RES (scalar logical) shows the GA results if true % % Output: % OPT_RTE (integer array) is the best route found by the algorithm % OPT_BRK (integer array) is the list of route break points (these specify the indices % into the route used to obtain the individual salesman routes) % MIN_DIST (scalar float) is the total distance traveled by the salesmen % % Route/Breakpoint Details: % If there are 10 cities and 3 salesmen, a possible route/break % combination might be: rte = [5 6 9 4 2 8 3 7], brks = [3 7] %

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