【摘要】 混流装配线调度问题是JIT生产中的一个重要问题。借鉴二进制遗传算法中的交叉操作过程,对传统的连续型粒子群算法进行改进,使其适用于离散问题的优化处理。然后以丰田公司的汽车组装调度函数作为目标函数,利用改进的离散粒子群算法进行求解。对比分析表明:新算法所得结果优于常用的目标追随法、遗传算法、模拟退火等方法。更多还原

【Abstract】 Solving the scheduling problem is a most important goal for JIT production systems.By referring to the crossover operations in the genetic algorithms,the classic particle swarm optimization(PSO) is adapted to discrete combination problems.Then taking the Toyota’s mixed-model scheduling function as the target function,the adapted discrete PSO algorithm is used to solve that problem,and the satisfactory feasible solutions are achieved.The comparison results showed that the solutions produced by PSO are better than that of Toyota’s Goal Chasing algorithm,genetic algorithm and simulated annealing algorithm.更多还原