Generalization of the MOACS algorithm for Many Objectives. An application to motorcycle distribution

Abstract

To solve many-objective routing problems, this paper generalizes the Multi-Objective Ant Colony System (MOACS) algorithm, a well-known Multi-Objective Ant Colony Optimization (MOACO) metaheuristic proposed in 2003. This Generalized MOACS algorithm is used to solve a Split-Delivery/Mixed-Fleet Vehicle Routing Problem (SD/MF-VRP) under different constraints, resulting from the mathematical modeling of a logistic problem: the distribution of motorcycles by a Paraguayan factory, considering several objective functions as: (1) total distribution cost, (2) total traveled distance, (3) total traveled time, and (4) nsatisfied demand. Experimental results using the proposed algorithm in weekly operations of the motorcycle factory prove the advantages of using the proposed algorithm, facilitating the work of the logistic planner, reducing the distribution cost and minimizing the time needed to satisfy customers.

Keywords

• Multiobjective Optimization; Many-Objective Optimization
• Vehicle Routing Problem; Ant Colony Optimization; Distribution