Modified bat algorithm for the multi-objective flexible job shop scheduling problem

Abstract

In this paper, a modified bat algorithm (MBA) is proposed for solving the multi-objective flexible job shop scheduling problem. Three different production performance indicators are considered which are the makespan, the total workload of machines and the critical machine workload. Firstly, to make the algorithm adaptive to the problem, the converting approaches are presented to implement the conversion between the continuous position vector and the discrete scheduling code. Secondly, an initialization scheme combining heuristics and random rule is introduced to ensure good quality and diversity of the initial population. Furthermore, five neighborhood structures are designed based on individual positions. Then, a local search algorithm is embedded into the BA to enhance the local searching ability. Finally, simulation results demonstrate the feasibility and effectiveness of our proposed algorithm.