Paper Info
Title
Multi-Objective Two-Echelon City Dispatching Problem With Mobile Satellites and Crowd-Shipping
Abstract
Recently, a two-echelon city dispatching model with mobile satellites (2ECD-MS) has been proposed to reduce costs effectively. However, in addition to costs, speeds of delivery to customers are increasingly demanding in urban dispatching. This work extends 2ECD-MS to 2ECD-MS-CS by adopting the crowd-shipping model in the second-echelon dispatching, which uses occasional drivers of private vehicles to deliver parcels to improve the delivery speed. Furthermore, existing works generally consider the optimization from a single aspect, e.g., the delivery company. However, the sustainable development of a logistics company must also focus on other subjects in logistics activities, such as customers and delivery employees. So, we define a multi-objective model considering company cost, customer satisfaction, and income satisfaction of crowd-shippers simultaneously. The multi-objective optimization problem of 2ECD-MS-CS is solved by a multi-directional evolutionary algorithm (MDEA). In MDEA, multiple neighborhood operators are designed and combined with the multi-directional search strategy to fully explore the Pareto Front. Finally, we generate 40 new 2ECD-MS-CS instances based on existing common vehicle routing datasets. Experimental results show that 2ECD-MS-CS reduces the average cost by 3.4% and improves the delivery speed by 42% against 2ECD-MS in 40 instances with different customer scales, numbers of mobile satellites, and geographic scopes. The proposed MDEA outperforms several popular multi-objective optimization algorithms in both convergence and diversity. These illustrate the advantages of 2ECD-MS-CS especially in terms of delivery speed and the effectiveness of the proposed MDEA.
Year
DOI
Venue
2022
10.1109/TITS.2022.3140351
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
Keywords
DocType
Volume
Optimization, Costs, Satellites, Dispatching, Companies, Logistics, Customer satisfaction, Crowd-shipping, multi-objective optimization, multi-directional search, two-echelon
Journal
23
Issue
ISSN
Citations 
9
1524-9050
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Yulin Lan101.35
Fagui Liu200.34
Wing W. Y. Ng300.34
Mengke Gui400.34
Chengqi Lai500.34