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    Comparison of Fuzzy Solution Approaches for a Bilevel Linear Programming Problem
    (Springer Science and Business Media Deutschland GmbH, 2023) Altınkaynak, Büşra; Göçken, Tolunay; Yeşilkaya, Murat; Birgören, Burak; Daş, Gülesin Sena
    In this study, we consider solution approaches used to solve the proposed bilevel linear programming model for an Industrial Symbiosis network. We first solve this model with the well-known Karush-Kuch-Tucker (KKT) approach. However, transforming a bilevel programming model with the KKT approach increases the number of variables and constraints. For this reason, we use the fuzzy programming approach and the fuzzy goal programming approaches as alternatives to the KKT approach. Next, we compare the results of the KKT approach with these methods and examine the suitability of these approaches to solve our bilevel problem. Unlike previous studies, which claimed that fuzzy approaches mostly outperform the KKT approach, in our case, the best solution is obtained with the KKT approach. This is most probably because these approaches ignore the hierarchical nature of the problem. We believe that more research on fuzzy approaches is needed to evaluate the suitability of these approaches for solving bilevel programming problems. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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    Direct solution of fuzzy project crashing problem with fuzzy decision variables using tabu search and simulated annealing algorithms
    (IGI Global, 2017) Göçken, Tolunay
    Project management is a very important field employed for scheduling activities and monitoring the progress, in competitive and fluctuating environments. Project crashing analysis is concerned with shortening the project duration time by accelerating some of its activities at an additional cost. In reality, because of uncertain environment conditions there can be ambiguity in the parameters of the problem. The uncertainty in the parameters can be modeled via fuzzy set theory. Using fuzzy models give the chance of better project scheduling with more stability under uncertain environmental factors. In this study, a fuzzy project crashing problem with fuzzy decision variable - occurrence time of events - and fuzzy normal activity duration times is handled. The fuzzy project crashing problem is solved without any transformation process by employing a fuzzy ranking method and the tabu search and simulated annealing algorithms. Copyright © 2017, IGI Global.
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    Improvement of a genetic algorithm approach for the solution of vehicle routing problem with time windows
    (Institute of Electrical and Electronics Engineers Inc., 2017) Göçken, Tolunay; Yaktubay, Meltem; Kiliç, Fatih
    In this study, Vehicle Routing Problem with Time Windows (VRPTW) with known customer demands, a single depot and identical vehicles, is considered. Minimizing the total distance and the total waiting time of the vehicles are determined as objective functions for VRPTW which is capable to serve the customers in a prespecified time interval. A hybridized version of genetic algorithm which is a metaheuristic solution technique with constructive heuristic methods is proposed to produce effective solutions for VRPTW. By using sweep algorithm in initial population generation phase of genetic algorithm, it is planned to begin the search with high quality solution sets and in this way, get more feasible solutions faster. A benchmark problem in the literature is solved and obtained results are compared with the results of genetic algorithm with the nearest neighbor algorithm based algorithm. It is observed that the proposed genetic algorithm beginning with sweep based initial population generation algorithm reaches more effective solutions. © 2017 IEEE.
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    SIMULATION OPTIMIZATION APPROACH TO PERIODIC REVIEW INVENTORY CONTROL SYSTEM WITH BACKORDERS
    (2020) Dosdoğru, Ayşe Tuğba; İpek, Aslı Boru; Göçken, Mustafa; Göçken, Tolunay
    In today's competitive world, companies should minimize cost while providing high quality goods.Companies generally try to reduce the level of inventory to minimize the cost and therefore they usuallyobserve shortage in practice. At this point, using of the right inventory control policy is the most effective andefficient way to reduce shortage. In inventory control policies, the basic question is to specify the size and thetiming of a replenishment order in supply chain members. Over the years, many advanced methods have beenapplied to answer these questions. Due to the difficulty of dealing with the uncertainties in supply chainenvironment, simulation optimization (SO) is used in this study to get the application of goals in supply chain.Although SO requires a great deal of understanding related with inventory control system, the use of SObrings such complex system within the grasp of managers. In this paper, SO is used to analyze the supplierselection and inventory control system simultaneously. The system results clearly reveals that the best valuesof inventory control variables and the most suitable suppliers can be determined by SO in a two echelonsupply chain model with backorder.
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    Zaman Pencereli Araç Rotalama Problemi Çözümü İçin Çok Amaçlı Genetik Algoritma Yaklaşımı
    (2018) Göçken, Tolunay; Yaktubay, Meltem; Kılıç, Fatih
    Bu çalışmada, talepleri bilinen müşterilerin, konumu bilinen bir deponun ve belirli sayıda aynıkapasiteye ve özelliklere sahip özdeş araçların bulunduğu klasik Araç Rotalama Probleminin(ARP) bir çeşidi olan Zaman Pencereli Araç Rotalama Problemi (ZPARP) ele alınmıştır.Müşterilere belirli bir zaman aralığında hizmet verilebilen ZPARP için toplam yolu ve araçsayısını minimize etmek amaç fonksiyonları olarak belirlenmiştir. ZPARP’ye etkin çözümlerüretilmesi amacı ile meta-sezgisel bir yöntem olan genetik algoritmanın sezgisel metotlarlamelezleştirilmiş bir uyarlaması önerilmiştir. Genetik algoritmanın başlangıç popülasyonuoluşturma aşamasında süpürme algoritması ve en yakın komşu tabanlı bir algoritma kullanılaraküretilen kaliteli çözüm kümeleriyle aramaya başlaması, böylece optimum sonuçlara daha hızlıulaşılması planlanmıştır. Genetik algoritmada başlangıç popülasyonları oluşturmada farklısezgisel yöntemlerin kullanılmasının istenilen sonuca bir etkisi olup olmadığı test edilmiştir.Literatürde var olan bir veri problemi çözülmüş, süpürme algoritmasını kullanan genetikalgoritma ile daha etkin sonuçlara ulaşıldığı görülmüştür.