{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T04:43:01Z","timestamp":1777696981188,"version":"3.51.4"},"reference-count":29,"publisher":"SAGE Publications","issue":"4","license":[{"start":{"date-parts":[[2025,5,22]],"date-time":"2025-05-22T00:00:00Z","timestamp":1747872000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Intelligent Decision Technologies"],"published-print":{"date-parts":[[2025,7]]},"abstract":"<jats:p>Electric Vehicles (EVs) are increasing rapidly owing to their high performance, low maintenance and emission-free in the environment. The location of Charging Stations (CS) is very crucial to the popularisation of EVs in urban areas, which requires optimal charging infrastructures. Moreover, battery charging is very essential for EVs at the locations of vehicle travel. Only specific areas are suitable for deploying the EV charging stations (EVCS), which increases the waiting time and distance of the EVs. Hence, the proposed Tuna-Fish optimization (TFO) based charge scheduling scheme is developed to identify the locations of the CS and schedule the EVs, which reduces the distance of EVs, and waiting time of EVs and improves the rate of charged EVs. Real engineering problems and benchmark functions are evaluated in this optimization and the low computation time is achieved to perform the output performance. The TFO-based charge scheduling scheme achieves efficient results and 0.15\u2005min of average waiting time for EVs, 29 charged EVs at a time, 24.4\u2005km Distance of EVs and 98.65\u2005W of remaining energy of the EVs are performed. This model compares various methods to achieve better results in 50 EVs, 100 EVs and 150 EVs. The performance of the optimization enhances the placement of CS and schedules the EVs.<\/jats:p>","DOI":"10.1177\/18724981251338072","type":"journal-article","created":{"date-parts":[[2025,5,22]],"date-time":"2025-05-22T03:02:08Z","timestamp":1747882928000},"page":"2099-2122","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Optimal placement of charging stations based on the charge scheduling optimization"],"prefix":"10.1177","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-6934-6096","authenticated-orcid":false,"given":"Shashank Kumar","family":"Jha","sequence":"first","affiliation":[{"name":"Energy Engineering Department, Central University of Jharkhand, Brambe Rd, Brambe, Jharkhand, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sumit Kumar","family":"Jha","sequence":"additional","affiliation":[{"name":"Energy Engineering, Central University of Jharkhand, Brambe Rd, Brambe, Jharkhand, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8001-5784","authenticated-orcid":false,"given":"Pankaj","family":"Mishra","sequence":"additional","affiliation":[{"name":"Electrical and Electronics Engineering,\u00a0Birla Institute of Technology, Jharkhand, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7354-8611","authenticated-orcid":false,"given":"Bishnu Mohan","family":"Jha","sequence":"additional","affiliation":[{"name":"Energy Engineering, Central University of Jharkhand, Brambe Rd, Brambe, Jharkhand, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2025,5,22]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3168830"},{"key":"e_1_3_3_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.egyr.2023.04.355"},{"key":"e_1_3_3_4_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3112847"},{"key":"e_1_3_3_5_2","unstructured":"HM Government. 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