Hybrid Distribution Dispatch of Automatic Delivery Vehicles and Electric Vehicles in Front Warehouse

Di Zhang (), Hongjie Lan () and Chuan Wang
Additional contact information
Di Zhang: Beijing Jiaotong University
Hongjie Lan: Beijing Jiaotong University
Chuan Wang: China State Shipbuilding Corporation, Limited (CSSC) 714th Research Institute

A chapter in LISS 2024, 2025, pp 317-336 from Springer

Abstract: Abstract Amidst the expansion of fresh e-commerce, the front warehouse model has risen, praised for its prompt delivery and superior products. However, escalating operational costs have led to losses and closures across various firms, making cost reduction and efficiency crucial for sustainability. Concurrently, as unmanned logistics advances, the advantages of unmanned vehicles become evident. This paper introduces a dual-objective optimization model for unmanned and electric vehicles’ scheduling, focusing on minimizing costs and delivery times. Utilizing the NSGA-II algorithm for three customer distribution scenarios, it examines vehicle speed and compensation ratio impacts. The findings provide strategic guidance for companies at different growth stages.

Keywords: Front warehouse; Automatic delivery vehicle; Hybrid scheduling; Path optimization (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:lnopch:978-981-96-9697-0_26

Ordering information: This item can be ordered from
http://www.springer.com/9789819696970

DOI: 10.1007/978-981-96-9697-0_26

Access Statistics for this chapter

More chapters in Lecture Notes in Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().