%多旅行商问题的matlab程序

function varargout = mtspf_ga(xy,dmat,salesmen,min_tour,pop_size,num_iter,show_prog,show_res)

% MTSPF_GA Fixed Multiple Traveling Salesmen Problem (M-TSP) Genetic Algorithm (GA)

% Finds a (near) optimal solution to a variation of the 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 individual cities

% and back to the original starting place)

%

% Summary:

% 1. Each salesman starts at the first point, and ends at the first

% point, but travels to a unique set of cities in between

% 2. Except for the first, each city is visited by exactly one salesman

%

% Note: The Fixed Start/End location is taken to be the first 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/end point

% POP_SIZE (scalar integer) is the size of the population (should be divisi ble 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 10 3 7], brks = [3 7]

% Taken together, these represent the solution [1 5 6 9 1][1 4 2 8 1][1 10 3 7 1],

% which designates the routes for the 3 salesmen as follows:

% . Salesman 1 travels from city 1 to 5 to 6 to 9 and back to 1

% . Salesman 2 travels from city 1 to 4 to 2 to 8 and back to 1

% . Salesman 3 travels from city 1 to 10 to 3 to 7 and back to 1

%

% 2D Example:

% n = 35;