基于改进粒子群算法的单产品多厂协同生产决策方法

A Single-Product Multi-Factory Collaborative Production Decision-Making Method Based on Improved Particle Swarm Optimization Algorithm

研究了单产品多厂协同生产决策问题。考虑实际情况中的生产能力和运输条件等约束因素,提出了一种改进粒子群算法(IPSO)来解决该问题。为了避免粒子群算法容易陷入局部最优的情况,算法中引入模拟退火的思路,允许在求解过程中以一定的概率接受比当前稍差的解。同时,采用一种椭圆形函数动态调节速度因子,使得粒子间的信息交换过程更加合理。最后,采用MATLAB对文中算例进行计算,并通过与遗传算法(GA)和标准粒子群算法(PSO)结果对比,验证了所提算法的有效性。

This paper studies the single-product multi-factory collaborative production decision-making problem.Considering the constraints of production capacity and transportation conditions in the actual situation,this paper proposes an improved particle swarm optimization algorithm(IPSO)to solve this problem.In order to prevent the particle swarm algorithm from easily falling into the local optimal situation,the algorithm introduces the idea of simulated annealing,which allows to accept a slightly worse solution than the current solution with a certain probability in the solution process.At the same time,an elliptic function is used to dynamically adjust the speed factor,which makes the information exchange process between particles more reasonable.Finally,Matlab is used to calculate the examples in the paper,and the effectiveness of the proposed algorithm is verified by comparing with the results of genetic algorithm(GA)and standard particle swarm optimization(PSO).