A Hybrid Metaheuristic Algorithm for the Green Vehicle Routing Problem in the Dynamic Environment

A Hybrid Metaheuristic Algorithm for the Green Vehicle Routing Problem in the Dynamic Environment

Elhassania Messaoud, Adiba El Bouzekri El Idrissi, Ahmed Elhilali Alaoui
Copyright: © 2021 |Pages: 19
DOI: 10.4018/IJAMC.2021100102
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Abstract

The main goal of this research is to combine the dynamic vehicle routing problem (DVRP), in which new information is received along the day, and the green vehicle routing problem (GVRP), which determines the routes of vehicles to serve a set of customers, while minimizing the total amount of the greenhouse gas. In this study, the customers must be serviced at their locations by a set of vehicles in real time by minimizing the carbon dioxide CO2. For that, the authors present the technique employed to estimate the amount of CO2 emissions and integrate it into the proposed mathematic model. Then they develop the resolution approach based on ant colony optimization (ACO) algorithm and a large neighborhood search (LNS) algorithm. The effectiveness of this approach is tested on a set of the static and dynamic green problems instances.
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Freight Transportation

Road transportation is very important for the economic development, but it is also harmful to the environment and human health because of the pollution, accidents, noise, resource consumption, land use deterioration, and climate change risk (Kovacs et al., 2015). On the environmental level, it is one of the hugest consumers of petroleum products and hence a prime creator of the existing harmful particles, including greenhouse gases and CO2 as the most prevalent of them, in the air. Nevertheless, a significant portion of freight transportation is carried out by trucks, which emit a large amount of pollutants. For that, the global communities have been activated under the umbrella of the “Green Transportation” or the “Sustainable Transport” paradigm, to reduce these emissions has been realized.

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