Solving Transport Problems

Towards Green Logistics

Walid Besbes, Diala Dhouib, Niaz Wassan, Emna Marrekchi, Walid Besbes, Diala Dhouib, Niaz Wassan, Emna Marrekchi

• Publisher: Wiley-ISTE
• Year: 2019
• Print ISBN: 9781786303899
• eBook ISBN: 9781119686767
• Edition: 1
• Topic: Ciencia de la computación
• Subtopic: Ingeniería computacional

Solving Transport Problems establishes fundamental points and good practice in resolving matters regarding green transportation. This is to prompt further research in conveyance issues by providing readers with new knowledge and grounds for integrated models and solution methods. Focusing on green transportation, this book covers various sub-topics and thus consists of diverse content. Traditionally, academia and transport practitioners have mainly concentrated on efficient fleet management to achieve economic benefits and better-quality service. More recently, due to growing public environmental concerns and the industry understanding of the issue, the academic community has started to address environmental issues. The studies of green transportation compiled in this book have identified certain areas of interest, such as references, viewpoints, algorithms and ideas. Solving Transport Problems is for researchers, environmental decision-makers and other concerned parties, to start discussion on developing optimized technology and alternative fuel-based integrated models for environmentally cleaner transport systems.

1
An Adaptive Large Neighborhood Search Heuristic for the Green Dial-a-Ride Problem

This chapter studies the Green Dial-a-Ride Problem (G-DARP) which represents an extension of the classical Dial-a-Ride problem by considering a limited driving range of vehicles in combination with limited refueling infrastructure. In the G-DARP, a vehicle is allowed to refuel from any alternative fuel station with partial fill-up to eliminate the risk of running out of fuel during a route. This problem particularly arises for agencies and companies that employ a fleet of Alternative Fuel Vehicles (AFVs) to transport people. We present a linear mixed-integer mathematical programming formulation and propose an effective Adaptive Large Neighborhood Search (ALNS) algorithm to solve the G-DARP. Computational experiments confirm that the proposed algorithm produces high-quality solutions in a cost-effective and green manner. Moreover, the analysis shows the benefit of using partial refueling in terms of reducing the total fuel and CO₂e emissions costs compared to the use of full refueling.

1.1. Introduction

Public transportation has an overwhelming volume within the centers of today’s dynamic cities, making it increasingly difficult to manage and plan. In this respect, customers’ satisfaction is one of the major factors that should be considered in the transport planning process. Unfortunately, people with disabilities often do not have equal opportunities to benefit from the services, due to accessibility and mobility complications. In practice, their circumstances should be carefully ...

Table of contents

• Cover
• Table of Contents
• Preface
• Acknowledgments
• 1 An Adaptive Large Neighborhood Search Heuristic for the Green Dial-a-Ride Problem
• 2 Role of Green Technology Vehicles in Road Transportation Emissions – Case of the UK
• 3 Transport Pooling: Moving Toward Green Distribution
• 4 A Ruin and Recreate Solution Method for a Lexicographic Vehicle Routing Problem Integrating Park-and-Loop and Car Sharing
• 5 An Overview of the Recent Solution Approaches in the Green Vehicle Routing Problem
• 6 Multi-Criteria Decision Aid for Green Modes of Crude Oil Transportation Using MACBETH: The Sfax Region Case
• 7 Green Reverse Logistics: Case of the Vehicle Routing Problem with Delivery and Collection Demands
• 8 An Improved DTC Induction Motor for Electric Vehicle Propulsion: An Intention to Provide a Comfortable Ride
• 9 Optimization in Multilevel Green Transportation Problems with Electrical Vehicles
• List of Authors
• Index
• End User License Agreement