Application of Tabu search to scheduling trucks in multiple doors cross-docking systems

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 the largest potential for improvement. In summary, the approach explored in this research offers significant opportunity to improve cross-dock operations through reducing storage of products.