说明：  模拟退火是 80 年代初发展起来的一种随机性组合优化方法。它模拟高温金属降温的热力学过程，并广泛应用于组合优化问题。基于模拟退火的粒子群优化算法是把模拟退火机制引入基本粒子群优化算法中，采用杂交粒子群优化算法中的杂交运算和带高斯变异的粒子群优化算法中的变异运算，以便进一步调整优化群体。
(Simulated annealing is a stochastic combinatorial optimization method developed in the early 1980s. It simulates the thermodynamic process of high temperature metal cooling and is widely used in combinatorial optimization problems. The particle swarm optimization algorithm based on simulated annealing introduces the simulated annealing mechanism into the basic particle swarm optimization algorithm, and adopts the hybrid operation in hybrid particle swarm optimization algorithm and the mutation operation in particle swarm optimization algorithm with Gaussian mutation, so as to further adjust the optimization population.)