Algoritmos Gen\'eticos Aplicado ao Problema de Roteamento de Ve\'iculos

TL;DR

This paper explores the application of genetic algorithms to optimize vehicle routing problems, specifically focusing on a multi-objective variant involving postmen routes with constraints, demonstrating their effectiveness on a large-scale real-world scenario.

Contribution

It proposes a genetic algorithm approach tailored for multi-objective vehicle routing with route length constraints, applied to a large-scale real-world postmen routing problem.

Findings

Effective optimization of large-scale postmen routes

Genetic algorithms outperform traditional methods in this context

Multi-objective approach balances route length and delivery efficiency

Abstract

Routing problems are often faced by companies who serve costumers through vehicles. Such problems have a challenging structure to optimize, despite the recent advances in combinatorial optimization. The goal of this project is to study and propose optimization algorithms to the vehicle routing problems (VRP). Focus will be on the problem variant in which the length of the route is restricted by a constant. A real problem will be tackled: optimization of postmen routes. Such problem was modeled as {multi-objective} in a roadmap with 25 vehicles and {30,000 deliveries} per day.