An adaptive shuffled frog-leaping algorithm for flexible flow shop scheduling problem with batch processing machines

Abstract

Batch Processing Machines (BPM) and transportation are seldom studied simultaneously in Flexible Flow Shop. In this study, Flexible Flow Shop Scheduling Problem (FFSP) with BPM at the last stage and transportation is considered and an adaptive shuffled frog-leaping algorithm (ASFLA) is proposed to minimize makespan. To produce high-quality solutions, a heuristic is employed to produce initial solution, two groups are formed by using all memeplexes, then an adaptive memeplex search is implemented, in which the number of searches is dynamically determined by the quality of the memeplex, an adaptive group search is also conducted by exchanging memeplexes or supporting of the worse memeplex. A novel population shuffling and the worst memeplex elimination are proposed. A number of computational experiments are executed to test the new strategies and performances of ASFLA. Computational results demonstrate that new strategies are effective and ASFLA is a very competitive algorithm for FFSP with BPM and transportation.