Two-level vehicle routing with cross-docking in a three-echelon supply chain: A genetic algorithm approach

被引:53
|
作者
Ahmadizar, Fardin [1 ]
Zeynivand, Mehdi [1 ]
Arkat, Jamal [1 ]
机构
[1] Univ Kurdistan, Dept Ind Engn, Sanandaj, Iran
关键词
Logistics; Cross-docking; Vehicle routing; Genetic algorithm; OF-THE-ART; LOCATION PROBLEM; NETWORK DESIGN; LOCAL SEARCH; MANAGEMENT; HEURISTICS; MODEL;
D O I
10.1016/j.apm.2015.03.005
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The cross-docking process, which can function as an efficient logistics strategy, includes three operations, namely receiving products from inbound vehicles, consolidating the products into groups according to their destinations, and shipping them on outbound vehicles. This process should be performed with minimum storage between operations. This paper presents a model that considers two-level vehicle routing together with cross-docking. By considering the transportation costs and the fact that a given product type may be supplied by different suppliers at different prices, the routing of inbound vehicles between cross-docks and suppliers in the pickup process and the routing of outbound vehicles between cross-docks and retailers in the delivery process are determined. The goal is to assign products to suppliers and cross-docks, to optimize the routes and schedules of inbound and outbound vehicles, and to consolidate products so that the sum of the purchasing, transportation and holding costs is minimized. A hybrid genetic algorithm is developed for the problem, and the algorithm performance is validated by several numerical examples. (C) 2015 Elsevier Inc. All rights reserved.
引用
收藏
页码:7065 / 7081
页数:17
相关论文
共 50 条
  • [21] Modified variable neighborhood search and genetic algorithm for profitable heterogeneous vehicle routing problem with cross-docking
    Baniamerian, Ali
    Bashiri, Mahdi
    Tavakkoli-Moghaddam, Reza
    APPLIED SOFT COMPUTING, 2019, 75 : 441 - 460
  • [22] A heuristic method for location-inventory-routing problem in a three-echelon supply chain system
    Saragih, Nova Indah
    Bahagia, Senator Nur
    Suprayogi
    Syabri, Ibnu
    COMPUTERS & INDUSTRIAL ENGINEERING, 2019, 127 : 875 - 886
  • [23] Multi-facilities Location and Allocation Problem of Three-echelon Supply Chain Based on an Improved Genetic Algorithm
    Liu, Zhishuo
    Li, Han
    Gao, Pengfei
    2016 IEEE 13TH INTERNATIONAL CONFERENCE ON E-BUSINESS ENGINEERING (ICEBE), 2016, : 139 - 144
  • [24] A robust possibilistic programming model for production-routing problem in a three-echelon supply chain
    Beheshtinia, Mohammad Ali
    Salmabadi, Narjes
    Rahimi, Somaye
    JOURNAL OF MODELLING IN MANAGEMENT, 2021, 16 (04) : 1328 - 1357
  • [25] The benefits of a cross-docking delivery strategy: a supply chain collaboration approach
    Kreng, Victor B.
    Chen, Fang-Tzu
    PRODUCTION PLANNING & CONTROL, 2008, 19 (03) : 229 - 241
  • [26] Two-phase Matheuristic for the vehicle routing problem with reverse cross-docking
    Aldy Gunawan
    Audrey Tedja Widjaja
    Pieter Vansteenwegen
    Vincent F. Yu
    Annals of Mathematics and Artificial Intelligence, 2022, 90 : 915 - 949
  • [27] Vehicle Routing Problem with Forward and Reverse Cross-Docking: Formulation and Matheuristic Approach
    Gunawan, Aldy
    Widjaja, Audrey Tedja
    Vansteenwegen, Pieter
    Yu, Vincent F.
    2021 IEEE 17TH INTERNATIONAL CONFERENCE ON AUTOMATION SCIENCE AND ENGINEERING (CASE), 2021, : 1467 - 1472
  • [28] Two-phase Matheuristic for the vehicle routing problem with reverse cross-docking
    Gunawan, Aldy
    Widjaja, Audrey Tedja
    Vansteenwegen, Pieter
    Yu, Vincent F.
    ANNALS OF MATHEMATICS AND ARTIFICIAL INTELLIGENCE, 2022, 90 (7-9) : 915 - 949
  • [29] A reliable location-inventory-routing three-echelon supply chain network under disruption risks
    Mohebban-Azad, Ehsan
    Abtahi, Amir-Reza
    Yousefi-Zenouz, Reza
    JOURNAL OF MODELLING IN MANAGEMENT, 2022, 17 (02) : 601 - 632
  • [30] A hybrid meta-heuristic algorithm for vehicle routing and packing problem with cross-docking
    İlker Küçükoğlu
    Nursel Öztürk
    Journal of Intelligent Manufacturing, 2019, 30 : 2927 - 2943