Modified self-adaptive local search algorithm for a biobjective permutation flowshop scheduling problem

Authors

ÇİĞDEM ALABAŞ USLU
BERNA DENGİZ
CANAN AĞLAN
İHSAN SABUNCUOĞLU

DOI

10.3906/elk-1811-40

Abstract

Interest in multiobjective permutation flow shop scheduling (PFSS) has increased in the last decade to ensure effective resource utilization. This study presents a modified self-adaptive local search (MSALS) algorithm for the biobjective permutation flow shop scheduling problem where both makespan and total flow time objectives are minimized. Compared to existing sophisticated heuristic algorithms, MSALS is quite simple to apply to different biobjective PFSS instances without requiring effort or time for parameter tuning. Computational experiments showed that MSALS is either superior to current heuristics for Pareto sets or is incomparable due to other performance indicators of multiobjective problems.

Keywords

Biobjective permutation flow shop, self-adaptive heuristic, parameter tuning

First Page

2730

Last Page

2745

Recommended Citation

USLU, ÇİĞDEM ALABAŞ; DENGİZ, BERNA; AĞLAN, CANAN; and SABUNCUOĞLU, İHSAN (2019) "Modified self-adaptive local search algorithm for a biobjective permutation flowshop scheduling problem," Turkish Journal of Electrical Engineering and Computer Sciences: Vol. 27: No. 4, Article 26. https://doi.org/10.3906/elk-1811-40
Available at: https://journals.tubitak.gov.tr/elektrik/vol27/iss4/26