An Improved Shuffled Frog Leaping Algorithm for Fuzzy Flow Shop Scheduling Problem

A new shuffled frog leap algorithm (NSFLA) is presented for the flow shop scheduling problem (FSSP) with uncertain processing time. A particle swarm optimization-like method is applied in the local search of SFLA, while a shuffle strategy where the information is periodically exchanged between complexes is used in global search. To cope with the problem that the local search of SFLA easily generates illegal solutions, two tracking strategies, i.e., randomization of the initial position in swap sequence constructing and random inserting of the swap operator, are proposed by means of the concepts of the swap operator and swap sequence. Numerical simulation results show the effectiveness of the NSFLA for fuzzy flow shop scheduling problem.