Heterojen filo üzerinde araç rotalama probleminin melez yaklaşımla uyum temalı çözümü
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Date
2020-11-05
Authors
Bulut, Nisanur
Journal Title
Journal ISSN
Volume Title
Publisher
Bursa Uludağ Üniversitesi
Abstract
Günümüz lojistik uygulamalarında çeşitlenen müşteri talepleri ve belirlenen yasal zorunluluklar sebebiyle araç rotalama işleminin kısıtları çeşitlenmiş ve rotalama karmaşıklığı giderek artmıştır. Firmalar müşteri teslimatlarını gerçekleştirirken düşük maliyetli ancak değişen koşullara uyum sağlayacak esnek ve kalıcı çözümlere ihtiyaç duymaktadır. Bu çalışmada farklı tipte taşınma ihtiyaçları oldukları bilinen müşteri taleplerinin, farklı kapasite ve özelliklerde araçlar içeren heterojen filo kullanılarak karşılanmasıyla ortaya çıkan tek depolu sıkı zaman pencereli heterojen filolu araç rotalama problemi ele alınmıştır. İptal edilen müşteri talepleri, kapanan yollar veya arızalanan araçların olması gibi çeşitli durumlarda yeni çözümler üretebilen hiyerarşik yapıda üç aşamalı bir karar destek sistemi tasarlanmıştır. Birinci aşamada müşteri talepleri en kısa yol mesafesine sahip olacak şekilde tavlama benzetimi algoritması kullanılarak gruplandırılmıştır. Bu gruplama yapılırken, her grubun toplam yol mesafesinin dengeli olması yani eşit olması hedeflenmiştir. İkinci aşamada araç atama modellemesi kullanılmıştır. Birinci aşamada gruplanan müşteri talepleri uygun tip ve özelliklerdeki araçlarla eşleştirilmiştir. Bu eşleştirme işlemi yapılırken problem kısıtlarına uygun optimal çözüm genetik algoritma yardımıyla araştırılmıştır. Üçüncü aşamadaysa ikinci aşamada bulunan optimal çözüm üzerinde lineer düzeltme yapılarak çözümün kalitesi artırılmaya çalışmıştır.
In today's logistics applications, the constraints of the vehicle routing process have diversified and the routing complexity has gradually increased due to the diversified customer demands and the determined legal requirements. Firms need low-cost but flexible and permanent solutions that will adapt to changing conditions while performing customer deliveries. In this study, the problem of single-warehouse heterogeneous fleet vehicle routing with tight time windows, which occurs when customer demands, which are known to have different types of transportation needs, are met by using a heterogeneous fleet containing vehicles with different capacities and characteristics. A hierarchical three-stage decision support system has been designed to produce new solutions in various situations such as canceled customer requests, closed roads or broken vehicles. In the first stage, customer demands are grouped using the simulated annealing algorithm to have the shortest path distance. While making this grouping, it is aimed that the total distance of each group is balanced, that is, equal. In the second stage, vehicle assignment modeling was used. The customer demands grouped in the first stage were matched with suitable types and features. While performing this matching process, the optimal solution suitable for the problem constraints was investigated with the help of genetic algorithm. In the third stage, the quality of the solution was tried to be increased by linear correction on the optimal solution in the second stage.
In today's logistics applications, the constraints of the vehicle routing process have diversified and the routing complexity has gradually increased due to the diversified customer demands and the determined legal requirements. Firms need low-cost but flexible and permanent solutions that will adapt to changing conditions while performing customer deliveries. In this study, the problem of single-warehouse heterogeneous fleet vehicle routing with tight time windows, which occurs when customer demands, which are known to have different types of transportation needs, are met by using a heterogeneous fleet containing vehicles with different capacities and characteristics. A hierarchical three-stage decision support system has been designed to produce new solutions in various situations such as canceled customer requests, closed roads or broken vehicles. In the first stage, customer demands are grouped using the simulated annealing algorithm to have the shortest path distance. While making this grouping, it is aimed that the total distance of each group is balanced, that is, equal. In the second stage, vehicle assignment modeling was used. The customer demands grouped in the first stage were matched with suitable types and features. While performing this matching process, the optimal solution suitable for the problem constraints was investigated with the help of genetic algorithm. In the third stage, the quality of the solution was tried to be increased by linear correction on the optimal solution in the second stage.
Description
Keywords
Zaman pencereli araç rotalama problemi, Çoklu gezgin satıcı problemi, Heterojen filo, Tavlama benzetimi, Genetik algoritma, Time window vehicle routing problem, Heterogeneous fleet, Simulated annealing, Genetic algorithm, Multiple traveling salesmen problem
Citation
Bulut, N. (2020). Heterojen filo üzerinde araç rotalama probleminin melez yaklaşımla uyum temalı çözümü. Yayınlanmamış yüksek lisans tezi. Bursa Uludağ Üniversitesi Fen Bilimleri Enstitüsü.