PSO_ACS混合算法求解VRPSPD问题及仿真

PSO-ACS Mixed Algorithm for Vehicle Routing Problem with Simultaneous Pick-up and Delivery

构造PSO_ACS混合算法求解同时送取货的车辆路径问题(VRPSPD),通过将ACS算法中的信息启发式因子和期望值启发式因子用解空间中的粒子位置动态表示,将PSO算法和ACS算法有机结合起来;利用PSO算法自适应改进ACS中的启发因子,从而提高蚁群算法的适应性。并用动态改变惯性权重的参数的方法加快PSO收敛速度。最终采用Dethloff的典型算例进行仿真实验,验证了混合算法的可行性和有效性,在求解最优解和收敛性能方面具有一定的优势。

A mixed algorithm called PSO_ACS was designed to solve the vehicle routing problem with simultaneous pick-up and delivery. The ACS and PSO were combined by defining information heuristic factor and expectation heuristic factor as the functions of the particle＇s positions, and the PSO algorithm was adopted to improve the heuristics parameters self-adaptively. This algorithm improves the convergent speed through changing the inertial weight of the PSO. The results of the numerical experiments on the Dethloff instances show that the mixed algorithm could get better value in efficient time.