An Enhanced Migrating Birds Optimization for a Lot-streaming Flow Shop Scheduling Problem

Migrating birds optimization (MBO) is a newly reported metaheuristic that has been proved effective in dealing with combinatorial optimization problems. In this paper, we propose an enhanced MBO (EMBO) to solve a lot-streaming flow shop scheduling problem with setup times, in which job-splitting and job scheduling are considered simultaneously. The objective is to minimize the makespan. In EMBO, a two-stage vector is employed to represent solutions in the swarm. Borrowing idea from artificial bee colony, a special neighbor structure is designed to create new candidates. Moreover, attempting to jump out of the local best, a new solution update scheme is introduced. Numerical tests are conducted and comparisons with other recent algorithms show the superiority of the proposed EMBO.