Genetic Algorithms for the Traveling Salesman Problem
Proceedings of the 1st International Conference on Genetic Algorithms
Vehicle routing scheduling for cross-docking in the supply chain
Computers and Industrial Engineering - Special issue: Logistics and supply chain management
International Journal of Computer Integrated Manufacturing
Expert Systems with Applications: An International Journal
Survey: Covering problems in facility location: A review
Computers and Industrial Engineering
Fuzzy-scorecard based logistics management in robust SCM
Computers and Industrial Engineering
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This research is concerned with an logistics system design which optimizes the performance of logistics system subject to required service levels both in the number of warehouse or distribution centers (W/D) and vehicle routing schedule. In this paper, the logistics system includes plants, W/D and customers. First, we formulated this problem using stochastic set-covering problem to determine the minimum number of W/D centers among a discrete set of location sites so that the probability of each customer to be covered is not less than a critical service level and solved this problem using 0-1 programming method. Then, we formulated a vehicle routing problem using an improved genetic algorithm and developed GUI-type programming based on three-step approaches such as: (1) clustering module which converges multi-supply center problem into single supply center problems, (2) improved vehicle routing, VRP module, and (3) GA-TSP module. For the users' conveniences, the sample results have been compared with those of existing methods. This research is strongly application oriented and the proposed model can be used to real world problems with some improvements.