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Application of Tabu Search to Scheduling Trucks in Multiple Doors Cross-Docking Systems

Nioosha Madani

Master's thesis (2013)

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Today's supply chain management performance has been affected by continuously increasing pressure of market forces. The pressure of market includes demands on increased flow of products and throughput with less amount of storage, also customers demand for more products with lower operational costs and more value-added services provided to customers. Supply chain is responsible in cost reduction and service levels increase by providing transshipments across its members. However supply chain has to face fluctuations of demands with the short available lead times. Physical problem of warehouse limitations and also inventory costs and shipping affect the performance of supply chain. In today's distribution strategies, the main goal is to provide a synchronization of customer chains and the suppliers. The objective is to reduce the inventory buffering between customers and suppliers. The idea of cross-docking is to receive different goods from a manufacturer for several end destinations and possibly consolidate the goods with other manufacturer's items for common final customers; then ship them in the earliest possible time. The focus of this research effort is to improve cross-dock operations with the goal of increasing the service performance levels and reducing costs. Specifically, metaheuristics algorithm of Tabu search is investigated for finding optimal sequence of incoming and outgoing trailers at cross-docks. This thesis reviews available research literature on cross-dock operations. Tabu search for the truck scheduling problem is presented along with results. Tabu search algorithm is investigated for the truck scheduling problem in the multiple doors cross-docking with unknown incoming and outgoing sequences. The objective of this research is to maximize the total direct transfer of products from a supplier to common final delivery destinations. The algorithm is implemented in C++ and analyzed using different problem instances. The results gained from algorithm of Tabu search are compared with other iterative heuristic descent method. The results indicate that the Tabu search performs significantly better than the descent method for large problem instances. In general, the results present that a metaheuristic algorithm of Tabu search for multiple or single door cross-docking offers thelargest potential for improvement. In summary, the approach explored in this research offers significant opportunity to improve cross-dock operations through reducing storage of products.


Cette recherche focus sur l'amélioration des cross-dockings en vue d'augmenter les niveaux de performance du service et de réduire les coûts. l'algorithme de la recherche avec tabous est étudiée pour trouver la séquence optimale d'entrée et sortie des remorques au cross-docking. L'objectif de cette recherche est de maximiser le nombre total de transferts directs entre le fournisseur et une destination finale commune de livraison. Dans les stratégies de distribution actuelles, l'objectif est de synchroniser les chaines du fabricant et du client. Le cross-docking implique de recevoir les produits d'un fournisseur pour plusieurs clients et d'occasionnellement consolider cela avec les produits d'autres fournisseurs pour des destinations finales de livraison communes. En résumé, l'approche examinée dans cette recherche donne une occasion significative pour l'amélioration des opérations au Cross-docking par la réduction du stockage des produits.

Department: Department of Mathematics and Industrial Engineering
Program: Génie industriel
Academic/Research Directors: Alain Hertz and Pierre Baptiste
PolyPublie URL: https://publications.polymtl.ca/1097/
Institution: École Polytechnique de Montréal
Date Deposited: 16 Jul 2013 15:44
Last Modified: 08 Apr 2024 08:39
Cite in APA 7: Madani, N. (2013). Application of Tabu Search to Scheduling Trucks in Multiple Doors Cross-Docking Systems [Master's thesis, École Polytechnique de Montréal]. PolyPublie. https://publications.polymtl.ca/1097/


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