Iranian Institute of Industrial Engineering Journal of Industrial and Systems Engineering 1735-8272 17 2 2025 04 01 Hybrid Ant Colony optimization and Variable Neighborhood Search algorithm for Electric and Fossil Fuel Vehicle Routing 26 43 209776 EN Nargesarges Khanlarzade 1Department of Industrial Engineering, Faculty of Engineering Management, Kermanshah University of Technology, Kermanshah, Iran Babak Yousefi Yegane 1Department of Industrial Engineering, Faculty of Engineering Management, Kermanshah University of Technology, Kermanshah, Iran 0000-0002-8844-8912 Journal Article 2024 05 13 The use of eco-friendly energies has gained significant attention in recent years due to their high importance in preserving the environment. This study examines the vehicle routing problem, utilizing two categories of vehicles: owned vehicles and rented vehicles. The rented vehicles exclusively consist of electric vehicles, while the owned vehicles include both electric and fossil fuel-powered ones. To encourage the adoption of electric vehicles and discourage the use of fossil fuel-powered vehicles, government incentives are implemented. This approach aims to mitigate the harmful environmental impacts associated with fossil fuel consumption. This pioneering concept is formulated as the Close-Open Mixed-fleet Electric Vehicle Routing Problem with time window (COMF-EVRP), with a detailed mathematical framework provided. In the absence of real data, the performance of the proposed algorithm is evaluated using numerical examples involving 30 vehicles: 5 rental electric vehicles, 10 owned electric vehicles, and 15 fossil fuel-powered vehicles. The test problems differ in customer distribution, including random, clustered, and a combination of both scenarios. Key parameters such as vehicle capacities, customer demands, and charging stations were also considered. Due to the complexity of the mathematical model, a meta-heuristic approach based on the ant colony optimization algorithm is proposed to solve the problem. To improve the quality of the obtained solutions, they undergo a variable neighborhood search procedure. The computational results indicate that the proposed solution procedures are capable of achieving high-quality solutions in reasonable CPU time. These findings suggest that transportation companies could enhance their operational efficiency by implementing similar strategies. https://www.jise.ir/article_209776_583c658d2276fa8c3dcb7cdd5ee78dee.pdf