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Abstract

Cross-docking is a logistics strategy that consolidates the products of different inbound trucksaccording to their destinations in order to reduce the inventory, order picking, and transportationcosts. It requires a high level of collaboration between inbound trucks, internal operations, andoutbound trucks. This article addresses the truck-to-door sequencing problem. Truck-to-doorsequencing has been studied by some researchers in different titles such as scheduling andsequencing of inbound and outbound trucks of the cross-dock center. However, previous studieshave not considered repeat truck holding pattern. Therefore, it is important to determine the doorsand the sequence of the inbound and outbound trucks that should be assigned in a cross-dockcenter. This paper focuses on optimizing truck-to-door sequencing with consideration of repeattruck holding pattern in inbound trucks in order to minimize makespan. Two methods areconsidered to solve this problem, including mathematical modeling and a heuristic algorithm. Inthe first method, a mixed integer-programming model is developed to minimize the makespan.Then, GAMS software is used to solve small-scale problems. In the second approach, a heuristicalgorithm is developed to find near-optimal solutions within the shortest time possible and thealgorithm is used to solve large-scale problems. The results of the mathematical model and theheuristic algorithm are slightly different and show the good quality of the presented heuristicalgorithm.

Item Type:	Article
Authors/Creators:	Ardakani, A and Fei, J and Beldar, P
Keywords:	cross docking, truck to door sequencing, multi door, dock repeat holding pattern, optimization, heuristic algorithm
Journal or Publication Title:	International Journal of Industrial Engineering Computations
Publisher:	Growing Science
ISSN:	1923-2926
DOI / ID Number:	https://doi.org/10.5267/j.ijiec.2019.10.001
Copyright Information:	© 2020 by the authors. Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0) http://creativecommons.org/licenses/by/4.0/
Related URLs:	Google Scholar: Fei, J UTAS Profile: Fei, J
Item Statistics:	View statistics for this item

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