An Effective Differential Evolution Algorithm for Solving Multi-Depot Vehicle Routing Problem: A Case Study of the Cassava Products Factory in Nakhon Ratchasima Province
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Abstract
This paper is to present an effective differential evolution algorithm (DE algorithm) for solving the Multi-Depot Vehicle Routing Problem (MDVRP). We apply the concept of an effective DE algorithm for solving MDVRP in a case study of the cassava products factory in Nakhon Ratchasima Province. The objective of this case is to minimize the total distance traveled. A proposed DE algorithm consists of four steps. The first step is to generate the Initial solution. The second step is the mutation process. The third step is the recombination process. The Final step is the selection process. The computational results showed that the proposed DE algorithm provided effective solutions by comparing with the two-phase heuristic (Cluster-First Route Second) and DE with ROV decoding. The proposed DE-Greedy Decoding method has 3.88% and 1.87% better transport routing efficiency than the two-phase heuristic and the DE-ROV Decoding algorithm, respectively.
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Articles published in Journal of Industrial Technology Ubon Ratchathani Rajabhat University both hard copy and electronically are belonged to the Journal.
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