Hybrid Flowshop Scheduling using Leaders and Followers: An Implementation with Iterated Greedy and Genetic Algorithm

Abstract

A hybrid flow shop is a kind of flow shop where multiple machines are available at some stages. This paper addresses the hybrid flow shop scheduling problem (HFSP) with identical parallel machines. We propose an algorithm based on the framework of Leaders and Followers (LaF), a recent metaheuristic that searches by two populations. We apply iterated greedy (IG) to the leader population for exploitation and genetic algorithm (GA) to the follower population for exploration. Investigations on the parameter setting and technical details of the algorithm are made by experiments using 240 public problem instances. Performance comparison with two recent algorithms verifies the solution quality and computational efficiency of the proposed algorithm.