Browsing by Author "Arvas, Mehmet Ali"

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Arc-Based Formulation and Grasp-Enhanced Iterated Greedy Algorithm for Identical Parallel Machine Scheduling with a Common Server
(Elsevier, 2026) Hamzadayi, Alper; Arvas, Mehmet Ali
The identical parallel machine scheduling problem with a single server and sequence-dependent setup times is a challenging optimization problem with important applications in manufacturing and service industries. In such environments, several machines depend on a common server to perform setup operations before production can begin, which creates strong interdependencies and demands more effective scheduling strategies. This characteristic highlights the practical relevance of the problem. The interaction between machine availability and server operations often becomes a critical bottleneck. This study introduces two complementary approaches. The first is an exact method based on a novel arc-based mixed-integer linear programming (ABF) model, which extends the modeling capability of existing formulations by capturing server-related constraints more effectively. The second is an approximation method built on an Iterated Greedy (IG) algorithm. The IG procedure is improved by two evaluation mechanisms: one model-based evaluation derived from the proposed ABF model, and another employing a greedy randomized adaptive search procedure (GRASP)-based strategy that integrates greedy selection, randomization, and reconstruction to enhance solution quality. Computational experiments are conducted on existing benchmark instances. The results show that the proposed ABF model performs well on small and medium-sized instances compared to existing exact methods, while the IG variants, particularly the proposed GRASP-based version, deliver strong performance against state-of-the-art metaheuristics developed for this problem. In addition, 21 new best-known solutions are reported, further demonstrating the effectiveness of the proposed approaches.
Distributed Assembly Permutation Flow Shop Problem; Single Seekers Society Algorithm
(Elsevier Sci Ltd, 2021) Hamzadayi, Alper; Arvas, Mehmet Ali; Elmi, Atabak
The distributed manufacturing and assembly systems have an important role at the point of overcoming the difficulties faced by today's mass-production industry. By using both of these systems together in the same production system, the advantages of this integration can make industries more flexible and stronger. Besides, optimizing these systems is more complicated since the multiple production systems can undoubtfully affect the production system's performance. In this paper, two new mixed-integer linear programming (MILP) models are proposed for the distributed assembly permutation flow shop problem (DAPFSP), inspiring by the multipletravelling salesman structure. Moreover, a single seekers society (SSS) algorithm is proposed for solving the DAPFSP to minimize the maximum completion time of all products. The performance of the proposed MILP models is evaluated using 900 small-sized benchmark instances. The proposed MILP models were effective and were able to find more optimal solutions or improve the best-found solutions for the small-sized DAPFSP benchmark instances. Similarly, the SSS algorithm is statistically compared with the best-known algorithms developed for solving the DAPFSP on 900 small and 810 large-sized benchmark instances. The proposed SSS algorithm shows superior performance compared to other algorithms in solving the small-sized DAPFSP instances in terms of finding better solutions. In addition, it is as effective as the best performing algorithms developed to solve the large-sized DAPFSP instances. Furthermore, the best-found solutions for 40 numbers of test problems reported to be improved in this paper.
New Solution Methods for the Distributed Assembly Permutation Flowshop Scheduling Problem
(2020) Arvas, Mehmet Ali; Hamzadayı, Alper
Bu tez çalışmasında hem dağıtılmış imalatın hem de dağıtılmış montaj sistemlerinin dikkate alındığı Dağıtılmış Montaj Hattı Permütasyon Akış Tipi Çizelgeleme Problemi ele alınmıştır. Üretim endüstrinin önemli bir problemi olan bu tür karma modelli montaj hattı problemlerindeki amaç, nihai ürünlerin elde edilme zamanını en aza indirmektir (diğer bir değişle makespanı en aza indirmektir). Bu tezde de söz konusu problem tipinin çözümünü en iyilemenin bazı farklı yolları tartışılmaktadır. Bu kapsamda, ilgili problem tipinin daha etkin bir şekilde çözülebilmesi için yeni karma tam sayılı doğrusal programlama modelleri önerilmiştir. Ayrıca hâlihazırda literatürde var olan sezgisel/meta sezgisel yöntemlere ilave olarak da bu tezde yeni bir meta sezgisel yöntem tasarlanmış ve geliştirilmiştir. Son olarak, önermiş olduğumuz matematiksel modeller, literatürde var olan aynı veri setleri ve aynı özellikteki bilgisayar kullanılarak ve yine literatürde var olan en iyi matematiksel modelle karşılaştırılmıştır. Yapılan deneyler sonucunda literatürde var olan en etkili matematiksel modelden daha etkili bir matematiksel model geliştirdiğimiz görülmüştür. Aynı şekilde tarafımızdan önerilen meta sezgisel yöntem ise, ilgili problem için oluşturulmuş 1710 tane örnek setine yönelik şu ana kadar tespit edilen en iyi çözümlerin sonuçları göz önünde bulundurularak istatistiksel karşılaştırma yapılmıştır. Yapılan deneyler neticesinde, problemin çözümüne yönelik şu ana kadar literatürde var olan yöntemlerden daha etkin bir meta sezgisel algoritma geliştirdiğimiz görülmüş ve ayrıca mevcut en iyi çözümlerden 40 tane daha iyi sonuç tarafımızca bulunmuş ve rapor edilmiştir.