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Bu çalışmada literatürde çalışılan en önemli kombinatoryal eniyileme problemlerinden biri olan stokastik araç rotalama problemi (SARP) ele alınmıştır. Bilindiği üzere klasik araç rotalama probleminde, araçların kapasiteleri ve müşterilerin talepleri bilinmektedir yani problem deterministiktir. Gerçek hayat problemlerinde problem parametreleri farklı durumlara göre değişkenlik gösterdiğinden, parametrelerin kesin değerlerinin bilinmesine az rastlanmaktadır. Bu yüzden belirtilen klasik araç rotalama probleminin belirsizlik koşulları altında formüle edilmesine ihtiyaç duyulmaktadır. Ele alınan çalışmada, müşteri taleplerinin belirsiz olduğu durumlar için, araç rotalama problemi analiz edilmiştir ve talepler stokastik olarak modelde değerlendirilmiştir. Değişken talep durumlarını incelemek için düzgün, üstel ve Poisson olmak üzere 3 farklı dağılım kullanılarak, bu dağılımların problemin çözümleri üzerindeki etkileri incelenmiştir. Hesaplama sonuçları için GAMS yazılımı kullanılmıştır ve çalışmanın sonunda ele alınan problemin stokastik ve deterministik modellerinin sonuçları kıyaslanmıştır.
This study addressed the stokastic vehicle rotating problem (SARP), which is one of the most important combinatory deduction problems in literature. As it is known, in the classic vehicle rotating problem, the capacity of the vehicles and customer demands are known, so the problem is deterministic. In real life problems, as the problem parameters vary according to different situations, there is little to know the exact values of the parameters. Therefore, the specified classic vehicle rotating problem needs to be formulated under uncertainty conditions. In the conducted study, for cases where customer requests are uncertain, the vehicle rotation problem was analyzed and requests were stocastically evaluated in the model. Using three different distribution, the correct, the superior and the Poisson, to study the variable demand situations, the effects of these distribution on the solutions of the problem have been studied. GAMS software was used for calculation results and the results of the stocastic and deterministic models of the problem addressed at the end of the study were compared.
In this study, stochastic vehicle routing problem (SVRP), which is one of the most important combinatorial optimization problems studied in the literature, is discussed. As it is known, the capacities of the vehicles and the demands of the customers are known in the classical vehicle routing problem, so the problem is deterministic. Since the problem parameters in real life problems vary according to the different situations, it is rare to know the exact values of the parameters. Therefore, there is a need to formulate the classical vehicle routing problem under uncertainty conditions. In this study, the vehicle routing problem is analyzed, and the demands are stochastically evaluated for the cases where customer demands are uncertain. In order to examine the variable demand conditions, the effects of these distributions on the solutions of the problem are investigated by using three different distributions, which are uniform, exponential, and Poisson. The GAMS software is used for computational results and the results of the stochastic and deterministic models of the problem are compared at the final part of the study.
Alan : Fen Bilimleri ve Matematik; Mühendislik
Dergi Türü : Ulusal
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