pso

  模拟退火算法——组合优化 模拟退火算法主要用于解决组和优化问题，它是模拟物理中晶体物质的退火过程而开发的一种优化算法。在对固体物质进行模拟退火处理时，通常先将它加温熔化，使其中的粒子可自由运动，然后随着温度的逐渐下降，粒子也逐渐形成了低能态的晶格。若在凝结点附近的温度下降速率足够慢，则固体物质一定会形成最低能态的基态。 对于组合优化问题来说，它也有这样的类似过程。组合优化问题解空间中的每一点都代表一个具有不同目标函数值的解。所谓优化，就是在解空间中寻找目标函数最小（大）解的过程。若把目标函数看成能量函数，某一控制参数视为温度 T，解空间当作形态空间，那么寻找基态的过程也就是求目标函数极小值的优化过程。 (Simulated annealing algorithm- combinatorial optimization Simulated annealing algorithm used to solve optimization problems and the group, it is the physical simulation of the crystal material in the annealing process and the development of an optimization algorithm. Solid substances in the simulated annealing process, it is usually heated it first melts, so that the particles are free to exercise, then gradually decreased as the temperature of the particles gradually formed a lower state of the lattice. If the temperature drops near the condensation rate slow enough, the solids will form the lowest energy state of the ground state. For combinatorial optimization problems, it also has such a similar process. Combinatorial optimization problem the solution space of each point represents a different objective function value of the solution. The so-called optimization, is in the solution space to find the minimum objective function (large) solution process. If the objective function a)