{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T03:37:28Z","timestamp":1790739448210,"version":"4.1.0"},"reference-count":44,"publisher":"Public Library of Science (PLoS)","issue":"1","license":[{"start":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T00:00:00Z","timestamp":1767312000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS One"],"abstract":"<jats:p>To address the challenges of insufficient battery power and service interruptions faced by electric buses (EBs) on urban and rural electric bus routes, this study proposes an urban and rural electric bus scheduling method considering mobile battery pack (MBP) deployment. This method involves deploying MBPs at one or more designated stations along the upward direction of the route, enabling EBs requiring en-route charging to pick up an MBP when passing through this station and returning it when passing through the corresponding downward stations on the return travel. A 0\u20131 mixed-integer programming model is formulated to achieve the joint optimization of the MBP deployment scheme, EB scheduling plan, and charging plan, targeting the minimization of the average daily operating cost of the route (including vehicle usage costs, MBP usage costs, charging costs, and battery degradation costs). Subsequently, the formulated model is addressed by employing a genetic algorithm with an elite retention strategy. Finally, a case study based on an actual urban and rural electric bus route is conducted and a comparison is made with the urban and rural electric bus scheduling method without MBPs. The results demonstrate that the urban and rural electric bus scheduling method considering mobile MBP deployment effectively reduces the average daily operating costs. Specifically, vehicle usage costs, charging costs, and battery degradation costs are reduced by 8.11%, 2.93%, and 21.06%, respectively, leading to an overall cost reduction of 5.20%. These findings confirm the significant potential of MBPs in enhancing the flexibility and economic viability of the urban and rural electric bus route.<\/jats:p>","DOI":"10.1371\/journal.pone.0339387","type":"journal-article","created":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T18:29:55Z","timestamp":1767378595000},"page":"e0339387","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":1,"title":["Optimization of urban and rural electric bus scheduling considering mobile battery pack 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