Bacterial Memetic Algorithm for Asymmetric Capacitated Vehicle-Routing Problem

The vehicle-routing problem (VRP) has many variants, including the most accurate models of real-life transportation tasks, making it one important mathematical problems in field logistics. Our goal was to design an algorithm that can race against recent solutions for VRP and capacitated (CVRP), while also being applicable with simulations real transports. is a variant bacterial memetic (BMA), which we improve upon novel operators better methods manual parameter optimization. key our performance balanced mixture global search evolutionary algorithms, local 2-OPT pseudo-global probabilistic construction algorithms. benefits from advantages all three resulting fast convergence avoidance minima. This first time BMA applied VRP, meaning had adapt method new problem. We compare some most-used on ABEFMP 1995 dataset. provide comparison results coronavirus herd immunity optimizer, genetic algorithm, hybridization neighborhood search, firefly enhanced ant colony optimization, variable search. performed data instances, yielding at least 30% improvement. present best result Belgium 2017 dataset future reference. Finally, show capable handling models. Here are illustrating significance different parameters.