{"ID":2839168,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2511.16547","arxiv_id":"2511.16547","title":"On the modular platoon-based vehicle-to-vehicle electric charging problem","abstract":"We formulate a mixed integer linear program (MILP) for a platoon-based vehicle-to-vehicle charging (PV2VC) technology designed for modular vehicles (MVs) and solve it with a genetic algorithm (GA). A set of numerical experiments with five scenarios are tested and the computational performance between the commercial software applied to the MILP model and the proposed GA are compared on a modified Sioux Falls network. By comparison with the optimal benchmark scenario, the results show that the PV2VC technology can save up to 11.07% in energy consumption, 11.65% in travel time, and 11.26% in total cost. For the PV2VC operational scenario, it would be more beneficial for long-distance vehicle routes with low initial state of charge, sparse charging facilities, and where travel time is perceived to be higher than energy consumption costs.","short_abstract":"We formulate a mixed integer linear program (MILP) for a platoon-based vehicle-to-vehicle charging (PV2VC) technology designed for modular vehicles (MVs) and solve it with a genetic algorithm (GA). A set of numerical experiments with five scenarios are tested and the computational performance between the commercial sof...","url_abs":"https://arxiv.org/abs/2511.16547","url_pdf":"https://arxiv.org/pdf/2511.16547v1","authors":"[\"Zhexi Fu\",\"Joseph Y. J. Chow\"]","published":"2025-11-20T17:00:08Z","proceeding":"cs.CY","tasks":"[\"cs.CY\"]","methods":"[]","has_code":false}