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emissions","volume":"29","author":"Yi","year":"2022","journal-title":"Environmental Science and Pollution Research"},{"key":"10.1016\/j.ejor.2026.01.015_bib0074","doi-asserted-by":"crossref","DOI":"10.1016\/j.rser.2023.113534","article-title":"Electric vehicles destination charging: An overview of charging tariffs, business models and coordination strategies","volume":"184","author":"Yong","year":"2023","journal-title":"Renewable and Sustainable Energy Reviews"},{"key":"10.1016\/j.ejor.2026.01.015_bib0075","series-title":"International conference on artificial evolution (evolution artificielle)","first-page":"89","article-title":"Maximizing the number of satisfied charging demands in electric vehicle charging scheduling problem","author":"Zaidi","year":"2022"},{"issue":"1","key":"10.1016\/j.ejor.2026.01.015_bib0076","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.ejor.2023.05.039","article-title":"Minimizing grid capacity in preemptive electric vehicle charging orchestration: Complexity, exact and heuristic approaches","volume":"312","author":"Zaidi","year":"2024","journal-title":"European Journal of Operational Research"},{"issue":"4","key":"10.1016\/j.ejor.2026.01.015_bib0077","doi-asserted-by":"crossref","DOI":"10.1016\/j.geits.2025.100283","article-title":"Multi-objective charging scheduling for electric vehicles at charging stations with renewable energy generation","volume":"4","author":"Zhang","year":"2025","journal-title":"Green Energy and Intelligent Transportation"},{"key":"10.1016\/j.ejor.2026.01.015_bib0078","doi-asserted-by":"crossref","DOI":"10.1016\/j.tre.2024.103698","article-title":"Reinforcement learning for electric vehicle charging scheduling: A systematic review","volume":"190","author":"Zhao","year":"2024","journal-title":"Transportation Research Part E: Logistics and Transportation 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