Solving tri-objective multistage hybrid flow shop scheduling problems using a discrete firefly algorithm

Abstract

Hybrid flow shop (HFS) scheduling problems turn into a fascinating area of research for the past several decades. However, most of the researchers consider only single objective and makespan is the most vital objective function. The real industrial scheduling problems involve multiple conflicting objectives. The HFS scheduling problems were proved to be NP-hard (non-deterministic polynomial time hard) problems. In this paper, we present a discrete firefly algorithm (DFA) to minimise the makespan, total flow time and machine idle time in a multistage HFS environment consisting of n jobs and k stages with identical parallel machines. The performance of the proposed algorithm is tested with a real industrial case study data and random problem instances. Computational results proved the effectiveness of the proposed algorithm.