A hybrid large-neighborhood search for a truck and drone delivery system with stochastic customer existence and time windows

Article type: Research Article

Authors: Teimoury, Ebrahim^{; *} | Rashid, Reza

Affiliations: Department of Industrial Engineering, Iran University of Science and Technology, Narmak, Tehran, Iran

Correspondence: [*] Corresponding author. Ebrahim Teimoury. Tel.: +98 21 7322 5022. E-mail: [email protected].

Abstract: In recent years, e-commerce has become increasingly popular, and consumers expect quick and affordable delivery, placing additional pressure on city logistics activities. An innovative approach is proposed to coordinate ground vehicles and drones for delivery services, which has gained tremendous attention from academia and logistic service providers. This paper introduces a variant of this problem: the two-echelon truck and drone routing problem, characterized by stochastic demand existence and soft time windows. A Markov chain is used to model the problem, and a linear mathematical model is presented. This work employs a hybrid large-neighborhood search approach. Numerous computational experiments are conducted to evaluate the performance of the proposed solution method, and the results demonstrate its efficacy.

Keywords: Last-mile delivery, truck and drone routing, stochastic optimization, Markov chain, large-neighborhood search

DOI: 10.3233/JIFS-224307

Journal: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 6, pp. 10197-10211, 2023