Dinamik Eş Zamanlı Toplamalı ve Dağıtmalı Araç Rotalama Problemi için Statik Periyodik Çözüm Stratejisi

Abstract

Günümüzde lojistik firmaları yüksek rekabet ortamının getirdiği baskılarla mücadele etmekte ve operasyonel maliyetleri düşürmeye çalışmaktadırlar. Aynı zamanda müşteriler, dağıtım ve toplama taleplerinin karşılanması için çok beklemek istememektedirler. Bu çalışmada, bahsedilen iki faktör statik periyodik çözüm stratejisiyle beraber ele alınmıştır. Problem, bir planlama dönemi içinde sürekli olarak gelen müşterilerin, toplama ve dağıtım taleplerinin aynı zamanda ve araçla karşılandığı “Dinamik Eş Zamanlı Toplamalı ve Dağıtmalı Araç Rotalama Problemi (DEZTDARP)” olarak modellenmiştir. Bununla beraber yeni ve ziyaret edilmemiş eski müşterileri göz önüne alarak rotalama problemlerini her zaman periyodu için tekrar tekrar çözen bir çözüm metodu önerilmiştir. Literatürde çok kullanılan bir sezgisel olan En Yakın Komşu Algoritması, her periyotta EZTDARP’lerini çözmek için kullanılmıştır. Talep dalgalanması, farklı sayıda müşteri, farklı rotalama periyotları gibi gerçek hayatta karşılaşılabilecek önemli hususlar probleme entegre edilmiştir. Sonuçlara bakıldığında, rotalama periyotlarının süresi arttığı zaman müşteri başı ortalama bekleme sürelerinin ciddi şekilde arttığı, ziyaret başı ortalama seyahat sürelerinin ise azaldığı görülmüştür. Rotalama planları günde 8 sefer yapıldığında müşteri başı ortalama bekleme süresi 5 dakika iken, plan sayısı 4 olduğunda bekleme süresi 66 dakikaya yükselmektedir. Daha fazla rotalama ise ziyaret başı fazladan 7 dakika ortalama seyahat süresine neden olmaktadır. Karar vericilerin hem firmalar hem de müşteriler için en iyi çözümü bulmalarına yardımcı olmak amacıyla farklı testler analiz edilmiş ve sonuçları açıklanmıştır.. 

Keywords

• Eş zamanlı toplamalı ve dağıtmalı araç rotalama problemi
• En yakın komşu algoritması
• Dinamik müşteri gelişleri
• Karar verme

A-Static-Periodic Solution Strategy for Dynamic Vehicle Routing Problem with Simultaneous Pickup and Delivery

Abstract

Nowadays, logistic companies are dealing with the pressure of a highly competitive environment and trying to reduce operational costs. At the same time, customers are requiring not to wait so long to get their delivery and pickup demands satisfied. In this study, these two factors are considered with a-static-periodic solution strategy. The problem is modelled as Dynamic Vehicle Routing Problem with Simultaneous Pickup and Delivery (DVRPSPD) where delivery and pickup demands of customers continuously arrived in a planning horizon are satisfied at the same time and by the same vehicle. Furthermore, we proposed a solution methodology based on solving routing problems repeatedly for each time period by considering new and unvisited previous customers. A well-known heuristic, the Nearest Neighbourhood Algorithm (NNA), is used to solve VRPSPDs in each time period. Important real-life aspects such as demand f luctuations, different number of customers, and routing periods are integrated into the problem. According to results, the average waiting times per customer significantly increase whereas average travel times per visit notably decrease when the length of time period increases. If routes are constructed 8 times in a day, each customer waits an average 5 minutes compared to 66 minutes if it is made 4 times in the day. More routing plans cause more than 7-minute average travel times per visit. Different test settings are analysed and the results are explained to help decision makers find the best solution for both companies and customers. 

Keywords

• Vehicle routing problem with simultaneous pickup and delivery
• The nearest neighbourhood algorithm
• Dynamic customer arrivals
• Decision making

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