Planning centralised logistics of products with specific characteristics under extreme situations, sudden changes and dynamic conditions

Abstract

A prominent situation in the transportation of goods to their destination is the need for unexpected changes to predetermined routes. In addition, when transporting goods to units with urgent needs have to be met. This problem of rerouting multiple vehicles under extreme situations when a route change is investigated in this paper. The delivery of medical products to nodes carrying infectious diseases is chosen as a case study whereas the vehicles visit each unit, the risk of contamination increases, and the vehicles need to meet the needs of the most urgent units first. For this case study, a modified test data is generated for dynamic problem, and it is solved with two-layered framework. The first layer is the static layer that the initial route is planned, and the second layer is the re-optimisation layer that is solved by using the proposed algorithm named as evolutionary algorithm operator-based Hybrid Genetic and Greedy algorithm (EAO-GA²). The proposed algorithm for the two layer frameworks studied in this research gave 83% better results than the problems solved for the static problem, and the total distance change in the dynamic problems studied was only 1.06%.

KEYWORDS:

• Logistics
• optimisation
• dynamic
• vehicle routing problem
• genetic algorithm
• greedy algorithm

Data availability statement

The data that support the findings of this study are openly available in https://doi.org/10.13140/RG.2.2.28284.21126

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. All other data that support the findings of this study are available on request from the author.

Disclosure statement

No potential conflict of interest was reported by the author(s).