对于以最小化最大完工时间为目标的置换流水车间调度问题,现有研究较少考虑学习效应对生产调度的影响,构建了具有学习效应的PFSP问题数学模型.采用ROV的编码方式,应用布谷鸟搜索算法进行离散优化问题求解.通过对Car类问题的大量仿真测试,表明了布谷鸟搜索算法求解该类问题的可行性和有效性.同时,证明了学习效应能够降低最大完工时间,从而提高生产效率.
This paper builds a mathematical model for solving the problem of permutation flow - shop scheduling with learning effect, whose objective is to minimize the Makespan. Cuckoo search (CS) algorithm, one of the latest nature - inspired metaheuristic algorithms, combining with the code rule based on Ranked Order Value is adopted to solve the discrete optimization problem. Simulation results of benchmark instances validate the feasibility and effectiveness of the CS algorithm. In addition, it is shown that the learning effect can reduce the Makespan and thus improve the productivity.