Browsing by Author "Duran, Ege"

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Çoklu dönem boyama ve gruplama problemi için optimizasyon ve sezgisel yaklaşımlar
(2022) Duran, Ege; Örnek, Mustafa Arslan; Öztürk, Cemalettin
Bu tezde, iplik boyama üreticisi olan firmada gerçek hayattaki bir problem için birden çok vardiyalı boyama ve harmanlama problemi ele alınmıştır. Makinelerin ağırlığına, üretim miktarına ve hacim kapasitesine ek olarak, iplikler büyük kazanlarda işleme alındığında flotte, renk türleri, renk yüzdeleri ve müşteri siparişlerinin kimyasal tarifi gibi bir dizi teknik boyama etkileşim kısıtlaması vardır. boya likörü olarak bilinen su, ayrıca aynı vardiyada boyama işlemine yardımcı olacak bir dizi kimyasal madde içerir. Bildiğimiz kadarıyla literatürde bu kombinatoryal optimizasyon problemini çözecek bir çalışma bulunmamaktadır. Bu çalışma, şirket için atanmamış işlerin ve kullanılan kazanların sayısını en aza indirmek için verimli bir çizelgeleme problemi yaratmayı amaçlamaktadır. Böylece problem için iki matematiksel model geliştirilmiş ve küçük, orta ve büyük boyutlu örnekler için optimal sonuçlar elde edilmiştir. Çalışılan problem NP-hard olduğundan, problemi çözmek için iki sezgisel algoritma da önerilmiştir. On altı deney ve rastgele seçim geliştirildi. Önerilen algoritmaların performansı detaylı bir şekilde karşılaştırılmıştır.
Citation - WoS: 2
Citation - Scopus: 4
Combinatorial optimization methods for yarn dyeing planning
(Springer, 2025) Ege Duran; Cemalettin Öztürk; Mustafa Arslan Ornek; Duran, Ege; Ozturk, Cemalettin; Ornek, M. Arslan
Managing yarn dyeing processes is one of the most challenging problems in the textile industry due to its computational complexity. This process combines characteristics of multidimensional knapsack bin packing and unrelated parallel machine scheduling problems. Multiple customer orders need to be combined as batches and assigned to different shifts of a limited number of machines. However several practical factors such as physical attributes of customer orders dyeing machine eligibility conditions like flotte color type chemical recipe and volume capacity of dye make this problem significantly unique. Furthermore alongside its economic aspects minimizing the waste of natural resources during the machine changeover and energy are sustainability concerns of the problem. The contradictory nature of these two makes the planning problem multi-objective which adds another complexity for planners. Hence in this paper we first propose a novel mathematical model for this scientifically highly challenging yet very practical problem from the textile industry. Then we propose Adaptive Large Neighbourhood Search (ALNS) algorithms to solve industrial-size instances of the problem. Our computational results show that the proposed algorithm provides near-optimal solutions in very short computational times. This paper provides significant contributions to flexible manufacturing research including a mixed-integer programming model for a novel industrial problem providing an effective and efficient adaptive large neighborhood search algorithm for delivering high-quality solutions quickly and addressing the inefficiencies of manual scheduling in textile companies, reducing a time-consuming planning task from hours to minutes. © 2025 Elsevier B.V. All rights reserved.
The Uniform Parallel Machine Scheduling Problem: A Case Study
(Springer Science and Business Media Deutschland GmbH, 2020) Ege Duran; Gizem Görgülü; Ayben Pınar Kuruç; İpek Gülhan; Murat Doğruyol; Hande Oztop; Adalet Oner; Öner, Adalet; Gülhan, İpek; Doğruyol, Murat Can; Kuruç, Ayben Pınar; Duran, Ege; Görgülü, Gizem; Öztop, Hande; M.N. Osman Zahid , R. Abd. Aziz , A.R. Yusoff , N. Mat Yahya , F. Abdul Aziz , M. Yazid Abu , N.M. Durakbasa , M.G. Gençyilmaz
In this study the uniform parallel machine scheduling problem with non-common due dates and sequence-dependent setup times is addressed for a real-life problem in the dye house of a hood manufacturer company. The aim of this study is to create an efficient scheduling tool for the company which minimizes lateness (earliness and tardiness) in the system and reduces the buffer stock caused by the lateness. A mathematical model is developed for the problem and optimal results are obtained for the small-sized instances. As the studied problem is NP-hard three heuristic algorithms are also proposed to solve larger instances. The performance of the proposed algorithms is evaluated with a detailed computational experiment. Furthermore a user-friendly decision support system (DSS) is developed using Excel VBA interface and proposed solution approaches are embedded in the DSS. The developed DSS enables users to make an efficient scheduling in very short computational time and provides the results with detailed schedule reports and Gantt charts. As this problem can be faced in various industrial areas the proposed solution approaches can also be applied to different sectors and factories. © 2022 Elsevier B.V. All rights reserved.
Whale Optimization Algorithm for Job Scheduling Problem
(Springer Science and Business Media Deutschland GmbH, 2023) Mert Paldrak; Gamze Erdem; Ege Duran; Paldrak, Mert; Duran, Ege; Erdem, Gamze; N.M. Durakbasa , M.G. Gençyılmaz
Meta-heuristics are widely used methods in OR literature. Whale Optimization Algorithm (WOA) is one of these meta-heuristic methods which is recently developed. The objective of this study is to find the best possible job schedule while minimizing the make-span (i.e. the length of time elapsed from the beginning of first job to the end of the last job.) of the system. This problem is initially solved by using Optimization Programming Language namely CPLEX Studio IDE 20.1.0. Then WOA which is a current meta-heuristic used to solve the same problem. Some toy instances of different sizes are created and the results obtained by using CPLEX and WOA are compared. Although in some studies in the literature WOA is used to solve job shop scheduling problems there is not a study which uses WOA as a solution methodology for parallel machine job scheduling problem with machine eligibility consideration to the best of our knowledge. Thus the main contribution of this study is to include machine eligibility to the conventional job scheduling problem and to use WOA while solving the corresponding problem. © 2023 Elsevier B.V. All rights reserved.