Waiting strategy for the vehicle routing problem with simultaneous pickup and delivery using genetic algorithm. (1st March 2021)

• Record Type: Journal Article
• Authors: Park, Hyungbin; Son, Dongmin; Koo, Bonwoo; Jeong, Bongju
• Is Part Of: Expert systems with applications. Volume 165(2021)
• Publication Date: 2021-03-01
• Subjects: Vehicle routing problem with simultaneous pickup and delivery -- Waiting strategy -- Rerouting indicator -- Genetic algorithm; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2020.113959
• Languages: English
• ISSNs: 0957-4174

Abstract

Highlights: We develop a mathematical model for vehicle routing problem with simultaneous pickup and delivery. We develop a genetic algorithm to solve the large-scale problems and validate its performance. We utilize the Waiting Strategy based on rerouting indicator to accommodate newly occurring orders. Abstract: With the development of information and telecommunication technology and the wide adoption of smartphones, consumers gradually change their purchase pattern toward online shopping. They can order products from their smartphones at any moment from any place, and the volume and variety of products delivered to consumers are increasing explosively. Companies in this industry need to set up the operational strategies to accommodate the increasing demand for delivery and return of products, and their focus should be the real-world vehicle routing problems with an additional consideration of the dynamic orders placed over time. This study proposes a waiting strategy for the vehicle routing problem with simultaneous pickup and delivery. This strategy implements an index called the rerouting indicator, which functions as a decision-making threshold to determine the rerouting point for real-time demands. For the most real-world-cases with complex problems, this study proposes a genetic algorithm to solve and validate its accuracy and performance by comparing the computational results. The significance and application of the waiting strategy are validated through several experiments, and the appropriate discretion by a decision maker can demonstrate the value of the proposed strategy.