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Formulation and implementation of solution algorithms for vehicle routing problems in emergency situations

Taxidou Andromachi

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Summary

In this phd thesis, we studied the vehicle routing problem for emergency situations in the cold supply chain. We solved the problem with suitable swarm intelligence algorithms. The above problem belongs to the general category of vehicle routing problems (VRP) and specifically belongs to the category of green vehicle routing problem (GVRP), aiming to minimize the cost of the route taking into account the environmental footprint. The aim of the relevant research is to solve the GVRP taking into account the different types of costs incurred during the transport of perishable products. More specific, we considered an application with vehicles with refrigerator mechanism, that transport goods such as food or vaccines, that demands specific required temperature conditions in order to store and transport with safety. In order to simulate the routes of refrigerated vehicles, we implement the green vehicle routing problem (GVRP) adapting it to the needs of the cold supply chain with an additional constraint of the maximum time that a truck can travel the route. The aim of the problem is to find the best route, the one with the minimum total cost and more specific to find the minimum route cost with other costs that occur from the problem’s structure. For the solution of the problem, we create hybrid variations of swarm intelligence algorithms in combination with local search algorithms.

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