simulatedannealing.m

这段代码使用了模拟退火的思想解决TSP问题。在这个仿真实验中解决了自定义的20个城市的TSP问题

function s = simulatedannealing(inputcities,initial_temperature,cooling_rate,threshold,numberofcitiestoswap)
%模拟退火算法。参数有输入城市数据，初始温度，冷却速率，阈值和交换城市数量。
%该部分的算法参考了网络和计算机学会期刊上的多篇论文。
global iterations;
temperature = initial_temperature;
initial_cities_to_swap = numberofcitiestoswap;
iterations = 1;
complete_temperature_iterations = 0;
previous_distance = distance(inputcities);
while iterations < threshold
    temp_cities = swapcities(inputcities,numberofcitiestoswap);
    current_distance = distance(temp_cities);
    diff = abs(current_distance - previous_distance);
    if current_distance < previous_distance
        inputcities = temp_cities;
        if rem(iterations,100) == 0
                plotcities(inputcities);
        end
        if complete_temperature_iterations >= 10
            temperature = cooling_rate*temperature;
            complete_temperature_iterations = 0;
        end
        numberofcitiestoswap = round(numberofcitiestoswap*exp(-diff/(iterations*temperature)));
        if numberofcitiestoswap == 0
            numberofcitiestoswap = 1;
        end
        previous_distance = current_distance;
        iterations = iterations + 1;
        complete_temperature_iterations = complete_temperature_iterations + 1;
    else
        if rand(1) < exp(-diff/(temperature))
            inputcities = temp_cities;
            if rem(iterations,100) == 0
                plotcities(inputcities);
            end
            numberofcitiestoswap = round(numberofcitiestoswap*exp(-diff/(iterations*temperature)));
            if numberofcitiestoswap == 0
                numberofcitiestoswap = 1;
            end
            previous_distance = current_distance;
            complete_temperature_iterations = complete_temperature_iterations + 1;
            iterations = iterations + 1;
        end
    end
end