A hybrid metaheuristic with applied to variants of the multicommodity traveling salesman problem with priority prizes

Abstract

In this project, we will address variants of the Multicommodity Traveling Salesman Problem with Priority Prize (PCVMP). The PCVMP consists of determining a route of delivery of goods considering the customer and the seller. The objective is to minimize total costs and, at the same time, satisfy customer preferences, maximising priorities in relation to the service order. Features such as multiple deposits, time windows and vehicles with capacity will be incorporated in the mathematical model of the literature, as well as in heuristic methods, in order to obtain solution approaches that are feasible in practice. These methods will be based on the Adaptive Biased Random-key Genetic Algorithm (A-BRKGA) metaheuristic, which has an online configuration process for the control flow and the tuning parameters of the method. The proposed models and methods will be implemented computationally and validated through computational experiments using available data and real data with information on traffic. Thus, it is expected to contribute to the literature, by proposing new models and metaheuristics for practical variants of the PCVMP. (AU)