A Discrete Firefly Algorithm to Solve a Rich Vehicle Routing Problem Modelling a Newspaper Distribution System with Recycling Policy

TL;DR

This paper models a complex newspaper distribution problem with recycling as a new asymmetric, clustered vehicle routing problem and introduces a novel discrete firefly algorithm that outperforms existing meta-heuristics.

Contribution

It is the first study of a rich vehicle routing problem with recycling, and it develops the first firefly algorithm application to such problems.

Findings

The discrete firefly algorithm outperforms evolutionary algorithms and simulated annealing.

A new benchmark with real geographical data was created for this problem.

The proposed method effectively handles complex constraints in vehicle routing.

Abstract

A real-world newspaper distribution problem with recycling policy is tackled in this work. In order to meet all the complex restrictions contained in such a problem, it has been modeled as a rich vehicle routing problem, which can be more specifically considered as an asymmetric and clustered vehicle routing problem with simultaneous pickup and deliveries, variable costs and forbidden paths (AC-VRP-SPDVCFP). This is the first study of such a problem in the literature. For this reason, a benchmark composed by 15 instances has been also proposed. In the design of this benchmark, real geographical positions have been used, located in the province of Bizkaia, Spain. For the proper treatment of this AC-VRP-SPDVCFP, a discrete firefly algorithm (DFA) has been developed. This application is the first application of the firefly algorithm to any rich vehicle routing problem. To prove that the proposed DFA is a promising technique, its performance has been compared with two other well-known techniques: an evolutionary algorithm and an evolutionary simulated annealing. Our results have shown that the DFA has outperformed these two classic meta-heuristics.