Greedy iterative genetic algorithm for the volume-based cross dock transportation problem associated with fixed charge Online publication date: Wed, 16-Dec-2020
by Solomon Joseph; R. Sridharan
International Journal of Logistics Systems and Management (IJLSM), Vol. 37, No. 4, 2020
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.
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