An Improved Discrete Migrating Birds Optimization Algorithm for the No-Wait Flow Shop Scheduling Problem

Abstract

An improved discrete migrating birds optimization (IDMBO) algorithm is presented in this work to solve the no-wait flow shop scheduling problem (NWFSSP) with makespan criterion. In the algorithm, all of the solutions in population are treated as birds aligned in a V formation named the leader and followers. To guarantee the quality and the diversity of initial population, the leader is provided by the standard deviation heuristic (SDH) algorithm, and the rest (the followers) are generated randomly. Given that IDMBO is a neighborhood-based search algorithm, the quality of algorithm depends heavily on the neighborhood structures, where the two variants of the hybrid multi-neighborhood strategy, which are multiply neighborhood structures embedded in variable neighborhood search (VNS) in different forms, are performed to generate the neighborhood solutions for leader and followers, respectively. Furthermore, the population reset mechanism is performed after a given number iterations without improving the current solution. The local search (LS) method can further ameliorate the quality of solutions. The computational study is conducted to analyze the efficiency of IDMBO algorithm on benchmarks designed by Reeve and Taillard. And the comparison results are shown that the presented algorithm is superior to several existing algorithms for NWFFSP.