20.500.12556/DKUM-97125 A combined genetic algorithm and A* search algorithm for the electric vehicle routing problem with time windows With growing environmental concerns, the focus on greenhouse gases (GHG) emissions in transportation has increased, and the combination of smart microgrids and electric vehicles (EVs) brings a new opportunity to solve this problem. Electric vehicle routing problem with time windows (EVRPTW) is an extension of the vehicle routing problem (VRP) problem, which can reach the combination of smart microgrids and EVs precisely by scheduling the EVs. However, the current genetic algorithm (GA) for solving this problem can easily fall into the dilemma of local optimization and slow iteration speed. In this paper, we present an integer hybrid planning model that introduces time of use and area price to enhance realism. We propose the GA-A* algorithm, which combines the A* algorithm and GA to improve global search capability and iteration speed. We conducted experiments on 16 benchmark cases, comparing the GA-A* algorithm with traditional GA and other search algorithms, results demonstrate significant enhancements in searchability and optimal solutions. In addition, we measured the grid load, and the model implements the vehicle-to-grid (V2G) mode, which serves as peak shaving and valley filling by integrating EVs into the grid for energy delivery and exchange through battery swapping. This research, ranging from model optimization to algorithm improvement, is an important step towards solving the EVRPTW problem and improving the environment. vehicle routing problem (VRP) electric vehicle optimization time windows spatiotemporal electricity price smart microgrids genetic algorithm (GA) A* search algorithm GA-A* algorithm promet emisije toplogrednih plinov pametne mreže elektroenergetski sistemi električna vozila genetski algoritem true false true Chair of Production Engineering (CPE), University of Maribor Faculty of Mechanical Engineering Angleški jezik Slovenski jezik https://apem-journal.org/ Content from this work may be used under the terms of the Creative Commons Attribution 4.0 International Licence (CC BY 4.0). Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. Članek v reviji 2026-02-19 08:32:51 2026-02-19 08:32:52 2026-02-20 03:13:30 0000-00-00 00:00:00 2023 0 0 str. 403-416 no. 4 Vol. 18 Dec. 2023 0000-00-00 Zaloznikova Objavljeno NiDoloceno 2023-09-25 2023-11-21 2023-12-28 621.31:519.17 268945667 10.14743/apem2023.4.481 1854-6250 APEM18-4_403-416.pdf APEM18-4_403-416.pdf 1 38E894260792C60AFF57DD25DACF1C80 388867443a5f4d4b245718e2ba3c981eea5b46ee65c1d7095ccc8afbe2e50d0c 5f4051e7-0d65-11f1-a5b8-00155d580e1a https://dk.um.si/Dokument.php?lang=slv&id=203491 https://apem-journal.org/Archives/2023/APEM18-4_403-416.pdf 0 66ff6011-0d65-11f1-a5b8-00155d580e1a https://dk.um.si/Dokument.php?lang=slv&id=203492 Fakulteta za strojništvo Advances in production engineering & management 0 0 0