Truck scheduling problems in the cross docking network

Author(s):  
Piya Hengmeechai ◽  
Takashi Irohara ◽  
Warisa Wisittipanich
2019 ◽  
Vol 33 (3) ◽  
pp. 420 ◽  
Author(s):  
Warisa Wisittipanich ◽  
Takashi Irohara ◽  
Piya Hengmeechai

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Zhanzhong Wang ◽  
Yue Lu ◽  
Liying Zhao ◽  
Ningbo Cao

The key of realizing the cross docking is to design the joint of inbound trucks and outbound trucks, so a proper sequence of trucks will make the cross-docking system much more efficient and need less makespan. A cross-docking system is proposed with multiple receiving and shipping dock doors. The objective is to find the best door assignments and the sequences of trucks in the principle of products distribution to minimize the total makespan of cross docking. To solve the problem that is regarded as a mixed integer linear programming (MILP) model, three metaheuristics, namely, harmony search (HS), improved harmony search (IHS), and genetic algorithm (GA), are proposed. Furthermore, the fixed parameters are optimized by Taguchi experiments to improve the accuracy of solutions further. Finally, several numerical examples are put forward to evaluate the performances of proposed algorithms.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Binghai Zhou ◽  
Shi Zong

Purpose The cross-docking strategy has a significant influence on supply chain and logistics efficiency. This paper aims to investigate the most suitable and efficient way to schedule the transfer of logistics activities and present a meta-heuristic method of the truck scheduling problem in cross-docking logistics. A truck scheduling problem with products time window is investigated with objectives of minimizing the total product transshipment time and earliness and tardiness cost of outbound trucks. Design/methodology/approach This research proposed a meta-heuristic method for the truck scheduling problem with products time window. To solve the problem, a lower bound of the problem is built through a novel two-stage Lagrangian relaxation problem and on account of the NP-hard nature of the truck scheduling problem, the novel red deer algorithm with the mechanism of the heuristic oscillating local search algorithm, as well as adaptive memory programming was proposed to overcome the inferior capability of the original red deer algorithm in the aspect of local search and run time. Findings Theory analysis and simulation experiments on an industrial case of a cross-docking center with a product’s time window are conducted in this paper. Satisfactory results show that the performance of the red deer algorithm is enhanced due to the mechanism of heuristic oscillating local search algorithm and adaptive memory programming and the proposed method efficiently solves the real-world size case of truck scheduling problems in cross-docking with product time window. Research limitations/implications The consideration of products time window has very realistic significance in different logistics applications such as cold-chain logistics and pharmaceutical supply chain. Furthermore, the novel adaptive memory red deer algorithm could be modified and applied to other complex optimization scheduling problems such as scheduling problems considering energy-efficiency or other logistics strategies. Originality/value For the first time in the truck scheduling problem with the cross-docking strategy, the product’s time window is considered. Furthermore, a mathematical model with objectives of minimizing the total product transshipment time and earliness and tardiness cost of outbound trucks is developed. To solve the proposed problem, a novel adaptive memory red deer algorithm with the mechanism of heuristic oscillating local search algorithm was proposed to overcome the inferior capability of genetic algorithm in the aspect of local search and run time.


2019 ◽  
Vol 11 (19) ◽  
pp. 5245 ◽  
Author(s):  
Oluwatosin Theophilus ◽  
Maxim A. Dulebenets ◽  
Junayed Pasha ◽  
Olumide F. Abioye ◽  
Masoud Kavoosi

Recent trends in the management of supply chains have witnessed an increasing implementation of the cross-docking strategy. The cross-docking strategy, being the one that can potentially improve supply chain operations, has received a lot of attention from researchers in recent years, especially over the last decade. Cross-docking involves the reception of inbound products, deconsolidation, sorting, consolidation, and shipping of the consolidated products to the end customers. The number of research efforts, aiming to study and improve the cross-docking operations, increases every year. While some studies discuss cross-docking as an integral part of a supply chain, other studies focus on the ways of making cross-docking terminals more efficient and propose different operations research techniques for various decision problems at cross-docking terminals. In order to identify the recent cross-docking trends, this study performs a state-of-the-art review with a particular focus on the truck scheduling problem at cross-docking terminals. A comprehensive evaluation of the reviewed studies is conducted, focusing on the major attributes of the cross-docking operations. These attributes include terminal shape considered, doors considered, door service mode considered, preemption, internal transportation mode used, temporary storage capacity, resource capacity, objectives considered, and solution methods adopted. Based on findings from the review of studies, some common issues are outlined and future research directions are proposed.


2015 ◽  
Vol 31 ◽  
pp. 30-47 ◽  
Author(s):  
Ali Mohtashami ◽  
Madjid Tavana ◽  
Francisco J. Santos-Arteaga ◽  
Ali Fallahian-Najafabadi

2012 ◽  
Vol 601 ◽  
pp. 470-475
Author(s):  
Jun Huang ◽  
Hai Bo Wang

Cross docking has been received a great attention in logistics field. This study uses graph theory to solve cross docking schedule problem. A specific example is given and a node oriented, graph partition model is introduced to exploit a new way in dealing with the cross docking schedule problem.


2018 ◽  
Vol 117 ◽  
pp. 29-40 ◽  
Author(s):  
Danyar Molavi ◽  
Amin Shahmardan ◽  
Mohsen S. Sajadieh

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