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Journals / Pamukkale Üniversitesi İşletme Araştırmaları Dergisi / 2023 / Cilt: 10 Sayı: 2

Solution of Permutation Flow Scheduling Problem with Grenade Explosion Method

Permütasyon Akış Tipi Çizelgeleme Probleminin El Bombası Patlatma Metodu ile Çözümü

Celal ÖZKALE
Kasım BAYNAL
Turgay ÖZTÜRK
Pages
491–510
Publication Date
2023-06-30
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Finally, it has been observed that GEM can reach acceptable results in reasonable time and can be used to solve these problems.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:For the efficient use of resources in production, the studies should be scheduled in the best way.
📊
Key Findings & Data:Then, the effect of the radius of the agent region, which distinguishes the method from other metaheuristics, on the method performance was analysed and its performance on the test problems presented by Taillard was examined regards the makespan criterion.
💡
Conclusion & Impact:Finally, it has been observed that GEM can reach acceptable results in reasonable time and can be used to solve these problems.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Permütasyon akış tipi çizelgeleme problemi · El Bombası Patlatma Metodu · Metasezgisel Yöntemler

Abstract

For the efficient use of resources in production, the studies should be scheduled in the best way. The permutation flowshop scheduling problem (PFSP), which has many applications in real life, has been attracting the attention of researchers for more than half a century. Grenade Explosion Method (GEM) is an evolutionary algorithm proposed by Ahrari et al., inspired by the explosions of grenades. In this study, GEM was adapted to solve permutation flowshop scheduling problems. Then, the effect of the radius of the agent region, which distinguishes the method from other metaheuristics, on the method performance was analysed and its performance on the test problems presented by Taillard was examined regards the makespan criterion. Finally, it has been observed that GEM can reach acceptable results in reasonable time and can be used to solve these problems.

Özet

Üretimde kaynakların verimli kullanımı için işlerin en iyi şekilde çizelgelenmesi gerekmektedir. Gerçek hayatta çok sayıda uygulaması bulunan permütasyon akış tipi çizelgeleme problemi (PATÇP) yarım asırdan uzun süredir araştırmacıların ilgisini çekmektedir. El Bombası Patlatma Metodu (EBPM) Ahrari ve arkadaşları tarafından el bombalarının patlamalarından esinlenerek geliştirilmiş evrimsel bir algoritmadır. Bu çalışmada EBPM, permütasyon akış tipi çizelgeleme problemlerinin çözümü için uyarlanmıştır. Daha sonra metodu diğer metasezgisellerden ayıran özellik olan ajan bölgesi yarıçapının metot performansına etkisi araştırılmış ve metodun maksimum tamamlanma zamanı performans ölçütüne göre Taillard tarafından geliştirilmiş olan test problemleri üzerindeki performansları incelenmiştir. Sonuç olarak EBPM’nin makul sürelerde kabul edilebilir sonuçlara ulaşabildiği ve PATÇP’lerin çözümünde kullanılabileceği görülmüştür.

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Cite This Article

ÖZKALE, C., BAYNAL, K., ÖZTÜRK, T. (2023). Solution of Permutation Flow Scheduling Problem with Grenade Explosion Method. Pamukkale Üniversitesi İşletme Araştırmaları Dergisi, Cilt: 10 Sayı: 2, 491–510. https://ajindex.com/articles/947638

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References (16)

  1. Aguiar, H., & Junior, O. (2015).
  2. Evolutionary Global Optimization, Manifolds and Applications. Studies in Systems, Decision and Control, 43, 17-18.
  3. Ahmadizar, F. (2012). A new ant colony algorithm for makespan minimization in permutation flow shops. Computers and Industrial Engineering, 63(2), 355-361. Ahrari,, Panahi, M. S., & Atai, A. (2009). GEM: A novel evolutionary optimization method with improved neighborhood search. Applied Mathematics and Computation, 210(2), 376-386.
  4. Ahrari, A., & Atai, A. (2010). Grenade Explosion Method - A novel tool for optimization of multimodal functions. Applied Soft Computing Journal, 10(4), 1132-1140.
  5. Ahrari, A., Saadatmand, M., Shariat-Panahi, M., & Atai, A. (2010). On the limitations of classical benchmark functions for evaluating robustness of evolutionary algorithms. Applied Mathematics and Computation, 215(9), 3222-3229.
  6. Ali, A., Gajpal, Y., & Elmekkawy, T. (2021). Distributed permutation flowshop scheduling problem with total completion time objective. OPSEARCH, 58(2), 425-447.
  7. Bacha, S. Z., Benatchba, K., & Tayeb, F. B.-S. (2022). Adaptive search space to generate a per-instance genetical gorithm for the permutation flow shop problem. Applied Soft Computing(124), 1-13.
  8. Baker, K., & Trietsch, D. (2009). Principles of Sequencing and Scheduling. John Wiley & Sons Inc. Bean, J. (1994). Genetic Algorithms and Random Keys for Sequencing and Optimization. HomeORSA Journal on Computing, 6(2), 154-160.
  9. Bouchekara, H., Chaib, ·., & Abido, ·. (2016). Multiobjective optimal power flow using a fuzzy based grenade explosion method. Energy Systems, 7, 699-721.
  10. Campbell, H., Dudek, R., & Smith, M. (1970, 6). A Heuristic Algorithm for the n Job, m Machine Sequencing Problem. Management Science, 16(10), 630-637. Ceri̇t, B., Onural, A. Ş., ve Yilmaz, B. (2005). Montaj ve işleme alt sistemlerini içeren bir esnek üretim sisteminin iki aşamalı çizelgelenmesi. Teknoloji, 8, 147-155.
  11. Cura, T. (2006). Modern Meta Sezgisel Teknikler ve Uygulamaları. İstanbul:
  12. Papatya Yayınları.
  13. Çiçekli, U. G., ve Bozkurt, s. (2016). Permütasyon Akış Tipi Çizelgeleme Probleminin Dağınık Arama İle Optimizasyonu. Ege Akademik Bakış, 16(Özel Sayı), 31-40.
  14. Dannenbring, D. (1977). An Evaluation of Flow Shop Sequencing Heuristics. Management Science, 23(11), 1149-1259.
  15. Dasgupta, P., & Das, S. (2015). A discrete inter-species cuckoo search for flowshop scheduling problems. Computers and Operations Research, 60, 111-120.
  16. Daya, M., & Al-Fawzan, M. (1998). A tabu s