Stochastic Multi-Objective Vehicle Routing Model in Green Environment With Customer Satisfaction
Author's Department
Mechanical Engineering Department
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https://doi.org/10.1109/tits.2022.3156685
Document Type
Research Article
Publication Title
IEEE Transactions on Intelligent Transportation Systems
Publication Date
1-1-2023
doi
10.1109/tits.2022.3156685
Abstract
The Vehicle Routing Problem (VRP) is one of the most studied combinatorial optimization problems in operations research that are classified as NP-hard. Introducing uncertainty to the problem increases the complexity of solving such problems. Sources of uncertainty in a VRP can be travel times, service times, and unpredictable demands of customers. Ignoring these sources may lead to inaccurate modeling of the VRP. Moreover, the area of green logistics and the environmental issues associated received significant attention. This paper aims to study the stochastic multi-objective Vehicle Routing Problem in a green environment. The stochastic Green VRP (GVRP) presented deals with three objectives simultaneously that consider economic, environmental, and social aspects. First, a new hybrid search algorithm to solve the VRP is presented and validated. The algorithm is then employed to solve the stochastic multi-objective GVRP. Pareto fronts were obtained, and trade-offs between the three objectives are presented. Furthermore, an analysis of the effect of customers’ time window relaxation is presented.
First Page
1337
Last Page
1355
Recommended Citation
APA Citation
Elgharably, N.
Easa, S.
Nassef, A.
&
El Damatty, A.
(2023). Stochastic Multi-Objective Vehicle Routing Model in Green Environment With Customer Satisfaction. IEEE Transactions on Intelligent Transportation Systems, 24(1), 1337–1355.
10.1109/tits.2022.3156685
https://fount.aucegypt.edu/faculty_journal_articles/4793
MLA Citation
Elgharably, Nayera, et al.
"Stochastic Multi-Objective Vehicle Routing Model in Green Environment With Customer Satisfaction." IEEE Transactions on Intelligent Transportation Systems, vol. 24,no. 1, 2023, pp. 1337–1355.
https://fount.aucegypt.edu/faculty_journal_articles/4793