A green vehicle routing problem with multi-depot, multi-tour, heterogeneous fleet and split deliveries: a mathematical model and heuristic approach

Ozgur Kabadurmus () and Mehmet S. Erdogan
Additional contact information
Ozgur Kabadurmus: Clemson University
Mehmet S. Erdogan: King’s College London

Journal of Combinatorial Optimization, 2023, vol. 45, issue 3, No 7, 29 pages

Abstract: Abstract Vehicle Routing Problem (VRP) is one of the most studied combinatorial optimization problems with many variants and extensions. This study introduces a novel VRP variant: Green Vehicle Routing Problem with Multi-Depot, Multi-Tour, Heterogeneous Fleet and Split Deliveries. In this problem, different vehicle types (heterogeneous fleet) with limited fleet sizes are allowed and the vehicles can be assigned to different depots (multi-depot). A vehicle can be used multiple times (multi-tour) and multiple vehicles can be assigned to a route (split delivery). The problem is formulated as a Mixed Integer Linear Programming (MILP) model to minimize the total carbon emissions. A Genetic Algorithm (GA), employing a MILP model and using niching and constraint handling techniques, is also developed to solve the problem effectively. The proposed algorithm has been tested on four hypothetical but realistic distribution networks. The results demonstrate the robustness and effectiveness of the proposed GA method on practical distribution scenarios.

Keywords: Green vehicle routing problem; Mixed integer linear programming; Genetic algorithm; Multi-tour; Split delivery (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://link.springer.com/10.1007/s10878-023-01016-7 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:jcomop:v:45:y:2023:i:3:d:10.1007_s10878-023-01016-7

Ordering information: This journal article can be ordered from
https://www.springer.com/journal/10878

DOI: 10.1007/s10878-023-01016-7

Access Statistics for this article

Journal of Combinatorial Optimization is currently edited by Thai, My T.

More articles in Journal of Combinatorial Optimization from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().