Truck scheduling problems in the cross docking network
Cross docking is a logistic management strategy for reducing storage level, inventory management cost, and customer delivery lead-time. In the large distribution network in which products are transferred through one or more cross docks, the decision of whether to synchronise inbound and outbound trucks for the whole network is crucial since it significantly impacts on supply chain performance. This study presents the novel mathematical model of truck scheduling problem in the cross docking network consisting of several cross docks and addresses the importance of synchronising the truck schedule in a network as a whole. The model is formulated as mixed integer programming (MIP) with an objective to find the optimal truck schedule and product transshipment to minimise the makespan. The results demonstrate that simultaneously optimising truck schedule throughout the network improves the solution quality compared to those obtained from models, that optimise the truck schedule in each cross dock sequentially.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/17427967
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Supplemental Notes:
- Copyright © 2018 Inderscience Enterprises Ltd.
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Authors:
- Wisittipanich, Warisa
- Irohara, Takashi
- Hengmeechai, Piya
- Publication Date: 2019
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Pagination: pp 420-439
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Serial:
- International Journal of Logistics Systems and Management
- Volume: 33
- Issue Number: 3
- Publisher: Inderscience Enterprises Limited
- ISSN: 1742-7967
- EISSN: 1742-7945
- Serial URL: http://www.inderscience.com/jhome.php?jcode=ijlsm
Subject/Index Terms
- TRT Terms: Loading and unloading; Logistics; Mixed integer programming; Optimization; Scheduling; Trucking
- Uncontrolled Terms: Transshipments
- Subject Areas: Freight Transportation; Motor Carriers; Operations and Traffic Management; Planning and Forecasting;
Filing Info
- Accession Number: 01717603
- Record Type: Publication
- Files: TRIS
- Created Date: Sep 19 2019 3:07PM