模拟退火算法解决TSP问题，用固体退火模拟组合优化问题，将内能E模拟为目标函数值f，温度T演化成控制参数t，即得到解组合优化问题的模拟退火算法：由初始解i和控制...

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模拟退火算法解决TSP问题，用固体退火模拟组合优化问题，将内能E模拟为目标函数值f，温度T演化成控制参数t，即得到解组合优化问题的模拟退火算法：由初始解i和控制参数初值t开始，对当前解重复“产生新解→计算目标函数差→接受或舍弃”的迭代，并逐步衰减t值，算法终止时的当前解即为所得近似最优解-Simulated annealing algorithm to solve the TSP problem, combined with solid-annealing simulation optimization problems, the internal energy E is modeled as the objective function value f, temperature T evolved into control parameter t, that is to be solutions of combinatorial optimization problems simulated annealing algorithm: from the initial solution i and control the parameters of the initial value t begin to repeat the current solution, " to generate new solutions of differential → → calculation of the objective function to accept or give up," iteration, and gradually decay t values, the algorithm is terminated shall be derived from the current approximate solution of the optimal solution