Date of Publication :17th March 2024

Abstract: This paper presents a unique approach to the Green Vehicle Routing Problem with Multiple Technologies and Partial Recharges (GVRP-MTPR) using the Flamingo Search Algorithm (FSA). GVRP-MTPR is a variation of the traditional Vehicle Routing Problem (VRP) characterized by the need for efficient routes considering the use of electric vehicles, multiple charging technologies, and partial recharges of the green vehicles. FSA is a swarm intelligence optimization algorithm that is inspired by the behaviors of flamingos, mainly the Foraging and Migrating behaviors. FSA has previously demonstrated excellent performance in a diverse set of tasks such as push-pull circuit problems, path planning problems, and network intrusion detection systems. In our proposed methodology, we use the Flamingo Search Algorithm (FSA) to tackle GVRP-MTPR. Our proposed model generates an initial set of solutions that is further optimized using the foraging and migrating behaviors of FSA. The model was tested on a dataset of 60 instances of varying customer and vehicle counts, order distributions, and topologies. Key metrics such as cost, fitness, number of iterations, and execution time are used in evaluating the performance of the model. The results highlight the competitiveness of the Flamingo Search Algorithm in addressing GVRP-MTPR, offering insights for the optimization of green vehicle routing in logistics and transportation operations.

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