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Solving the cumulative vehicle routing problem with the mimetic algorithm

Kamperi Angeliki

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Summary

A humanitarian supply chain is the process of planning and implementing the transport and storage of goods, materials and information from the point of origin to the point of consumption in order to bring relief to affected and vulnerable people. It adopts the need for rapid service and delivery of critical goods after a disaster and minimizing loss of life and damage. The pandemic highlighted all the weaknesses in the supply chain and the need for rapid service and delivery of critical goods after a disaster became evident. Thus, this thesis deals with the Cumulative Capacitated Vehicle Routing Problem which is one of the most important problems related to the distribution of goods in humanitarian supply chain. It is a transportation problem that arises when the objective is to minimize the sum of arrival times to customers, instead of the classical path length, with capacity constraints. An evolutionary algorithm, hybrid genetic or memetic, was used to solve the problem. The algorithm incorporates a local search procedure to intensify the search for solutions and is implemented in the MATLAB environment. Finally, the results of the problem are presented in detail, which involve 2 variations of the algorithm on 34 datasets.

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