Adoption of genetic algorithm for cross-docking scheduling with time window

L. Yang, Ka Man Lee

Research output: Chapter in book / Conference proceedingChapter in an edited book (as author)Academic research


Cross-docking is widely adopted as an alternative to traditional warehousing in many industries. It consolidates different deliveries from suppliers into specified shipments catered for respective customers, thus reducing transportation and inventory holding costs. This book chapter addresses the scheduling problem of delivery where the products are expected to ship from suppliers to cross-docking faculties to customers within time window. For generating online delivery scheduling for the distribution network, the problem, which is formulated with the objective of minimising the inventory, transportation and penalty cost, is solved by genetic algorithm. Experiments were conducted to study the robustness of the model and the performance of the important parameters. From the results, it was also found that as the number of deliveries, pickups, cross-docks, time horizon and product type increase, the number of variables involved increases which in turn increase the complexity of the model. With higher number of variables, the computational time elapsed increase tremendously and total cost increases with the number of product types.
Original languageEnglish
Title of host publicationDecision-making for supply chain integration : supply chain integration
Number of pages22
ISBN (Electronic)1447140338, 9781447140337
ISBN (Print)9781447140320
Publication statusPublished - 2012

Publication series

NameDecision engineering


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