An Efficient Two-Objective Hybrid Local Search Algorithm for Solving the Fuel Consumption Vehicle Routing Problem

Weizhen Rao,Shengbin Wang,Feng Liu

doi:10.1155/2016/3713918

Abstract

The classical model of vehicle routing problem (VRP) generally minimizes either the total vehicle travelling distance or the total number of dispatched vehicles. Due to the increased importance of environmental sustainability, one variant of VRPs that minimizes the total vehicle fuel consumption has gained much attention. The resulting fuel consumption VRP (FCVRP) becomes increasingly important yet difficult. We present a mixed integer programming model for the FCVRP, and fuel consumption is measured through the degree of road gradient. Complexity analysis of FCVRP is presented through analogy with the capacitated VRP. To tackle the FCVRP’s computational intractability, we propose an efficient two-objective hybrid local search algorithm (TOHLS). TOHLS is based on a hybrid local search algorithm (HLS) that is also used to solve FCVRP. Based on the Golden CVRP benchmarks, 60 FCVRP instances are generated and tested. Finally, the computational results show that the proposed TOHLS significantly outperforms the HLS.

Highlights

In recent years, consequences from natural resource depletion and environmental degradation have made sustainability a more important objective than profitability for public and private transportation systems
We focus on the fuel consumption VRP (FCVRP) and provide a mixed integer programming (MIP) model in which fuel consumption is measured by the degree of road gradient
We study the FCVRP in which road gradient is considered as one of the factors to measure fuel consumption

Summary

Introduction

Consequences from natural resource depletion and environmental degradation have made sustainability a more important objective than profitability for public and private transportation systems. Logistics service providers (LSPs) are paying increasing attention to the environmental externalities of the transportation operations [1], for example, fuel consumption and carbon dioxide equivalent (CO2e) emissions. These emissions can cause a lot of serious problems such as respiratory diseases and global warming. Minimizing the CO2e emissions from trucks as well as other types of vehicles while simultaneously completing the required transportation tasks has always been a key issue for these LSPs in the past two decades. This paper aims to provide an insight and a methodology to efficiently resolve this issue

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Conclusion