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

ALABAŞ USLU, ÇİĞDEM; Dengiz, Berna; Aglan, CANAN; SABUNCUOĞLU, İHSAN

doi:10.3906/elk-1811-40

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

Atıf İçin Kopyala

ALABAŞ USLU Ç., Dengiz B., Aglan C., SABUNCUOĞLU İ.

TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES, cilt.27, sa.4, ss.2730-2745, 2019 (SCI-Expanded)

Yayın Türü: Makale / Tam Makale
Cilt numarası: 27 Sayı: 4
Basım Tarihi: 2019
Doi Numarası: 10.3906/elk-1811-40
Dergi Adı: TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES
Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, TR DİZİN (ULAKBİM)
Sayfa Sayıları: ss.2730-2745
Marmara Üniversitesi Adresli: Evet

Özet

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.