A Novel Multi-Objective Inventory Routing Problem with Backhaul Orders in a Multi-Attribute Multigraph Considering Access Tax <sup>*</sup>

Rural areas face significant logistical challenges, including inadequate infrastructure, safety risks, and high transfer costs. Traditional inventory routing models often overlook these complexities, particularly the need for alternative routes and backhaul integration, where routes include deliveries and pickups. This study introduces a Multi-Objective Inventory Routing Problem in a Multigraph with Backhauls (MO-IRPMGB) and employs the Non-dominated Sorting Genetic Algorithm II (NSGA-II) for optimization, achieving average savings of 7% to 14%.

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Publication Details

Published
2025-06-24
DOI
https://doi.org/10.23919/ecc65951.2025.11187200
Primary Topic
Optimization and Packing Problems
Type
article
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article

A Novel Multi-Objective Inventory Routing Problem with Backhaul Orders in a Multi-Attribute Multigraph Considering Access Tax *

F. J. Moreno, Soheila Saeidi, Evangelos I. Kaisar
Optimization and Packing Problems
article

A Novel Multi-Objective Inventory Routing Problem with Backhaul Orders in a Multi-Attribute Multigraph Considering Access Tax *

F. J. Moreno, Soheila Saeidi, Evangelos I. Kaisar
article en

Abstract

Rural areas face significant logistical challenges, including inadequate infrastructure, safety risks, and high transfer costs. Traditional inventory routing models often overlook these complexities, particularly the need for alternative routes and backhaul integration, where routes include deliveries and pickups. This study introduces a Multi-Objective Inventory Routing Problem in a Multigraph with Backhauls (MO-IRPMGB) and employs the Non-dominated Sorting Genetic Algorithm II (NSGA-II) for optimization, achieving average savings of 7% to 14%.

Florida Atlantic University (US)
Openalex Percentile: Top 59%
Optimization and Packing Problems
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