Çiğdem Alabaş USLU, Berna DENGİZ, Canan AĞLAN, İhsan SABUNCUOĞLU

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

ISSN: 1300-0632
Yayın Aralığı: Yılda 6 Sayı
Yayıncı: TÜBİTAK

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.

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