%0 Journal Article %@ 18724981 %A Rahman, I. %A Vasant, P.M. %A Singh, B.S.M. %A Abdullah-Al-Wadud, M. %D 2016 %F scholars:7147 %I IOS Press %J Intelligent Decision Technologies %K Artificial intelligence; Carbon; Charging (batteries); Electric power transmission networks; Hybrid vehicles; Optimization; Plug-in electric vehicles; Smart power grids; Vehicles; Wind power, Literature reviews; Metaheuristic; PHEV; Smart grid; Swarm Intelligence, Plug-in hybrid vehicles %N 2 %P 149-163 %R 10.3233/IDT-150245 %T Novel metaheuristic optimization strategies for plug-in hybrid electric vehicles: A holistic review %U https://khub.utp.edu.my/scholars/7147/ %V 10 %X Hybrid Vehicles have experienced major modifications since the last decade. Smart grid success with combination of renewable energy exclusively depends upon the large-scale penetration of Plug-in Hybrid Electric Vehicles (PHEVs) for a sustainable and carbon-free transportation. Recent technical studies regarding various optimization strategies related to PHEV integrated smart grid; such as control and battery charging, vehicle-to-grid (V2G), unit commitment, charging infrastructures, integration of solar and wind energy and demand management prove that electrification of transportation as a rapidly growing field of research. This work presents a holistic review of all substantial research applying metaheuritics optimization for plug-inhybrid electric vehicles. A summary on future perspective of metaheuristic algorithms is also provided, covering Cuckoo Search (CS), Harmony Search (HS), Artificial Bee Colony (ABC), etc. with a comprehensive reviews on previously applied methods and their performance for solving different real-world problems in the domain of PHEVs. Moreover, significant shifts towards hybrid and hyper metaheuristics are also highlighted. © 2016 IOS Press and the authors. All rights reserved. %Z cited By 13