A matheuristic approach for the Pollution-Routing Problem

TL;DR

This paper introduces a hybrid matheuristic method for the Pollution-Routing Problem, optimizing vehicle routes and speeds to minimize environmental and operational costs, and extends the approach to related green VRP variants.

Contribution

It presents a novel hybrid approach combining local search and integer programming for the PRP, improving solution quality over previous methods.

Findings

The proposed method outperforms existing algorithms in solution quality.

New improved solutions for PRP and related variants are reported.

The approach effectively integrates route and speed decisions for environmental benefits.

Abstract

This paper deals with the Pollution-Routing Problem (PRP), a Vehicle Routing Problem (VRP) with environmental considerations, recently introduced in the literature by [Bektas and Laporte (2011), Transport. Res. B-Meth. 45 (8), 1232-1250]. The objective is to minimize operational and environmental costs while respecting capacity constraints and service time windows. Costs are based on driver wages and fuel consumption, which depends on many factors, such as travel distance and vehicle load. The vehicle speeds are considered as decision variables. They complement routing decisions, impacting the total cost, the travel time between locations, and thus the set of feasible routes. We propose a method which combines a local search-based metaheuristic with an integer programming approach over a set covering formulation and a recursive speed-optimization algorithm. This hybridization enables to integrate more tightly route and speed decisions. Moreover, two other "green" VRP variants, the Fuel Consumption VRP (FCVRP) and the Energy Minimizing VRP (EMVRP), are addressed. The proposed method compares very favorably with previous algorithms from the literature and many new improved solutions are reported.