A Clustering Algorithm For The Capacitated Vehicle Routing Problems With Stochastic Demands

Year 2022, Volume: 10 Issue: 2, 955 - 959, 26.12.2022

Melis Alpaslan Takan , Çerkez Ağayeva

https://doi.org/10.18586/msufbd.1218311

Abstract

In today’s world, logistics problems are crucial for the supply chain management. The vehicle routing problems are one of the most studied combinatorial optimization problems in the logistics literature. In real life applications, all of the parameters of the problem may not be known. In this paper, we considered the capacitated vehicle routing problem with stochastic demands. Uniform and normal distributions were analyzed on customer demands to observe the stochastic nature of the problem. These methods were compared by using GAMS with different test problems which were taken from the literature. The clustering analysis including the K-means algorithm also applied on large-sized test problems. All of the obtained results were presented in detail.

Keywords

Clustering Analysis, K-Means, Modelling, Stochastic Demand, VRP

Stokastik Talepli Kapasite Kısıtlı Araç Rotalama Problemleri için Bir Kümeleme Algoritması

Abstract

Günümüz dünyasında, tedarik zinciri yönetimi için lojistik problemler çok kritiktir. Araç rotalama problemi, lojistik literatüründe en çok çalışılan kombinatoryal optimizasyon problemlerinden biridir. Gerçek hayat uygulamalarında problemin tüm parametreleri bilinmeyebilir. Bu çalışmada, stokastik talepli kapasite kısıtlı araç rotalama problemi ele alınmıştır. Problemin stokastik yapısını gözlemlemek için müşteri talepleri düzgün ve normal dağılımlar ile analiz edilmiştir. Bu yöntemler, literatürden alınan farklı test problemleri ile GAMS kullanılarak karşılaştırılmıştır. Büyük boyutlu test problemleri için k-ortalamalar algoritmasını içeren kümeleme analizi uygulanmıştır. Elde edilen tüm sonuçlar ayrıntılı olarak gösterilmiştir.

Keywords

Kümeleme Analizi, K-Ortalamalar, Modelleme, Stokastik Talep, ARP

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