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Memory-based variable neighborhood search for green vehicle routing problem with passing-by drivers: a comprehensive
Lei Cao1, Chun-Ming Ye1, Ran Cheng2
1School of Business, University of Shanghai for Science and Technology, Shanghai, 200093 China.
Complex & Intelligent Systems
|February 14, 2022
Summary
This study introduces a new crowdsourcing logistics model using professional and occasional drivers for efficient parcel delivery. The innovative approach benefits all stakeholders, including customers and drivers, by optimizing delivery routes and compensation.
Area of Science:
- Operations Research
- Logistics Management
- Supply Chain Optimization
Background:
- Traditional delivery models face challenges in efficiency and cost-effectiveness.
- Crowdsourcing offers a flexible approach to supplement professional delivery fleets.
- Balancing stakeholder interests in a hybrid delivery system is complex.
Purpose of the Study:
- To develop a comprehensive, multi-layer model for a hybrid business delivery system.
- To optimize delivery operations considering professional and occasional drivers.
- To ensure satisfactory solutions for platform owners, customers, professional drivers, occasional drivers, and authorities.
Main Methods:
- A multi-layer comprehensive model was developed to represent the delivery system.
- An improved Variable Neighborhood Search (VNS) algorithm with memory-based restart was introduced.
- The VNS algorithm was tuned using Taguchi experiments and validated on benchmark and real-life instances.
Main Results:
- The proposed hybrid delivery model demonstrated advantages over traditional and single-delivery methods.
- The improved VNS algorithm effectively solved the complex optimization problem.
- Experimental results confirmed the effectiveness of the proposed strategies and delivery model.
Conclusions:
- The hybrid crowdsourcing logistics model offers a superior alternative to traditional delivery systems.
- The developed VNS algorithm provides an efficient solution for optimizing hybrid delivery networks.
- This research provides a practical framework for enhancing efficiency and stakeholder satisfaction in logistics.
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