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Greedy iterative genetic algorithm for the volume-based cross dock transportation problem associated with fixed charge

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  • Solomon Joseph
  • R. Sridharan

Abstract

Cross docking is a distribution method wherein the products from inbound vehicles are loaded directly onto outbound vehicles with a minor or no storage in between. The fixed charge cross dock transportation problem (FCCDTP) involves determining the optimal method of loading and routing the vehicles in a cross dock system with minimal fixed and variable cost of transportation. In this paper, the FCCDTP with the volume-based quantification of products is formulated as a mixed integer linear programming model. The model is solved using the optimisation software LINGO solver, the proposed GA with variable neighbourhood search (GA-VNS) meta-heuristic and the proposed greedy iterative genetic algorithm (GIGA) meta-heuristic. The data for the problems are obtained from a real-life logistics company. The analysis of results reveals that the proposed GIGA meta-heuristic provides lesser total transportation cost as compared to the GA-VNS meta-heuristic.

Suggested Citation

  • Solomon Joseph & R. Sridharan, 2020. "Greedy iterative genetic algorithm for the volume-based cross dock transportation problem associated with fixed charge," International Journal of Logistics Systems and Management, Inderscience Enterprises Ltd, vol. 37(4), pages 488-539.
    • Handle: RePEc:ids:ijlsma:v:37:y:2020:i:4:p:488-539
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