Abstract

To develop a non-polluting and sustainable city, urban administrators encourage logistics companies to use electric vehicles instead of conventional (i.e., fuel-based) vehicles for transportation services. However, electric energy-based limitations pose a new challenge in designing reasonable visiting routes that are essential for the daily operations of companies. Therefore, this paper investigates a real-world electric vehicle routing problem (VRP) raised by a logistics company. The problem combines the features of the capacitated VRP, the VRP with time windows, the heterogeneous fleet VRP, the multi-trip VRP, and the electric VRP with charging stations. To solve such a complicated problem, a heuristic approach based on the adaptive large neighborhood search (ALNS) and integer programming is proposed in this paper. Specifically, a charging station adjustment heuristic and a departure time adjustment heuristic are devised to decrease the total operational cost. Furthermore, the best solution obtained by the ALNS is improved by integer programming. Twenty instances generated from real-world data were used to validate the effectiveness of the proposed algorithm. The results demonstrate that using our algorithm can save 7.52% of operational cost.

Highlights

  • With industrial development and urbanization, air pollution in cities has become increasingly serious in recent years

  • In the proposed algorithm, the minimal and average of the total operational cost obtained by the adaptive large neighborhood search (ALNS) was not smaller than that improved by the integer programming (IP); the relative gap between the two algorithm components in the proposed algorithm was between 0% (R7 and R9) and 1.49% (R6), and the average relative gap was 0.40%

  • This paper develops a heuristic approach to solve a real-world electric vehicle routing problem (EVRP) proposed by a logistics company in Wuhan, China

Read more

Summary

Introduction

With industrial development and urbanization, air pollution in cities has become increasingly serious in recent years. A major cause of air pollution in cities is the large number of conventional motor vehicles with internal combustion engines that run on diesel or gasoline. They emit carbon oxides, nitrogen oxides and particulate matters that cause air pollution. Delivers up customer parcels within predefined windows, and finishes at the problem, a fleetor of picks heterogeneous electric vehicles departs from time the distribution center, delivers or center. The objective to minimize the of time the go its to charging stations as well the distribution center to fullyischarge its battery in sum a fixed acquisition costs used vehicles, the travel ofthe vehicles, the waiting at customers and (e.g., 30 min).

Illustration
Literature Review
Problem Description
Solution Approach
Construction of Initial Solution
Penalty Functions
Removal Heuristics
Shaw Removal Heuristic
Worst Removal Heuristic
Historical Knowledge Node Removal Heuristic
Insertion Heuristics
Basic Greedy Insertion Heuristic
Deep Greedy Insertion Heuristic
Regret-k Insertion Heuristic
Choosing a Removal and Insertion Heuristic
Acceptance Criteria
Local Search
Labeling
Departure Time Adjustment Heuristic
4.10. Set-Partitioning Model
Computational Experiments
Construction of Test Instances
Parameter Settings
Performance Analysis of ALNS
Comparison with Company’s Algorithm
Findings
Conclusions and Future Research

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.