Multi-Depot Pickup and Delivery Problem with Resource Sharing

Xiangyang Guan,Xiaoyue Liu,Lingyu Ran,Yong Wang,Yajie Zou

doi:10.1155/2021/5182989

Abstract

Resource sharing (RS) integrated into the optimization of multi-depot pickup and delivery problem (MDPDP) can greatly reduce the logistics operating cost and required transportation resources by reconfiguring the logistics network. This study formulates and solves an MDPDP with RS (MDPDPRS). First, a bi-objective mathematical programming model that minimizes the logistics cost and the number of vehicles is constructed, in which vehicles are allowed to be used multiple times by one or multiple logistics facilities. Second, a two-stage hybrid algorithm composed of a k-means clustering algorithm, a Clark-Wright (CW) algorithm, and a nondominated sorting genetic algorithm II (NSGA-II) is designed. The k-means algorithm is adopted in the first stage to reallocate customers to logistics facilities according to the Manhattan distance between them, by which the computational complexity of solving the MDPDPRS is reduced. In the second stage, CW and NSGA-II are adopted jointly to optimize the vehicle routes and find the Pareto optimal solutions. CW algorithm is used to select the initial solution, which can increase the speed of finding the optimal solution during NSGA-II. Fast nondominated sorting operator and elite strategy selection operator are utilized to maintain the diversity of solutions in NSGA-II. Third, benchmark tests are conducted to verify the performance and effectiveness of the proposed two-stage hybrid algorithm, and numerical results prove that the proposed methodology outperforms the standard NSGA-II and multi-objective particle swarm optimization algorithm. Finally, optimization results of a real-world logistics network from Chongqing confirm the applicability of the mathematical model and the designed solution algorithm. Solving the MDPDPRS provides a management tool for logistics enterprises to improve resource configuration and optimize logistics operation efficiency.

Highlights

With the advancement of information technology and Internet of ings, the logistics industry is playing an increasingly important role in the development of modern businesses [1, 2]
In consideration of the aforementioned shortcomings, the main contributions of this study to multi-depot pickup and delivery problem with RS (MDPDPRS) are as follows: (1) Characteristics of resource sharing (RS), MDVRPPD, and MDVRPPDTW are comprehensively incorporated to enrich the research on MDPDPRS. (2) On the basis of RS, this study proposes and tests that vehicles can be used multiple times and that customer information can be shared to save the transportation resources of logistics networks, which are considered in the proposed mathematical model
C23, C22, C6, C16, and C2 are served by DC1 before clustering; they are served by DC3

Summary

Introduction

With the advancement of information technology and Internet of ings, the logistics industry is playing an increasingly important role in the development of modern businesses [1, 2]. Customers send out a series of requests for delivery and pickup services, and logistics service providers (LSPs) design service plans and arrange vehicles for these requests to deliver or pickup goods [5, 6]. Efficient logistics service plan can improve the operation efficiency of LSPs and resource utilization [7, 8]. Erefore, making an effective logistics service plan with resource sharing (RS) is essential, which helps to reduce the operating cost for logistics facilities and promotes the development of green logistics and provides better logistics services for consumers [9, 10]. In the traditional MDVRPPD, each vehicle performs only one type of activity in the service route, which may be delivering or picking up goods [16,17,18]

Methods

Results

Conclusion