A microcomputer based decision support tool for assigning dock doors in freight yards
Proceedings of the 12th annual conference on Computers and industrial engineering
An optimal solution to a dock door assignment problem
Proceedings of the 14th annual conference on Computers and industrial engineering
Modern heuristic techniques for combinatorial problems
Modern heuristic techniques for combinatorial problems
Best Practice Simulated Annealing for the Airline Crew Scheduling Problem
Journal of Heuristics
Reducing Labor Costs in an LTL Crossdocking Terminal
Operations Research
Suggestions for China' logistics parks based on Japan's experience
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
Expert Systems with Applications: An International Journal
Multi-objective genetic-based algorithms for a cross-docking scheduling problem
Applied Soft Computing
Computers and Operations Research
Analysis of different approaches to cross-dock truck scheduling with truck arrival time uncertainty
Computers and Industrial Engineering
Consensus-based decision support for multicriteria group decision making
Computers and Industrial Engineering
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This paper addresses an evaluation of new heuristics solution procedures for the location of cross-docks and distribution centers in supply chain network design. The model is characterized by multiple product families, a central manufacturing plant site, multiple cross-docking and distribution center sites, and retail outlets which demand multiple units of several commodities. This paper describes two heuristics that generate globally feasible, near optimal distribution system design and utilization strategies utilizing the simulated annealing (SA) methodology. This study makes two important contributions. First, we continue the study of location planning for the cross-dock and distribution center supply chain network design problem. Second, we systematically evaluate the computational performance of this network design location model under more sophisticated heuristic control parameter settings to better understand interaction effects among the various factors comprising our experimental design, and present convergence results. The central idea of the paper is to evaluate the impact of geometric control mechanism vis-a-vis more sophisticated ones on solution time, quality, and convergence for two new heuristics. Our results suggest that integrating traditional simulated annealing with TABU search is recommended for this supply chain network design and location problem.