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With respect to the FJS-AGV problem, a heuristic-assisted deep Q-network (HA-DQN) algorithm is proposed, which leverages heuristic rules to enable the decision agent to perform multiple actions at each decision point, which includes determining the responses to the following questions: Which operation should be processed next? On which machine? By which AGV? This decision mechanism enables the agent to make more informed decisions, leading to improved performance and resource allocation in the FJS-AGV system. The practicability of the proposed FJS-AGV model and the efficiency of the HA-DQN algorithm in solving the FJS-AGV problem are verified through various international benchmarks. Specifically, when solving instances in a large benchmark, the HA-DQN algorithm yields a significant 12.63% reduction in makespan compared with that when traditional heuristics are employed.<\/jats:p>","DOI":"10.1007\/s40747-025-01828-6","type":"journal-article","created":{"date-parts":[[2025,3,17]],"date-time":"2025-03-17T16:35:07Z","timestamp":1742229307000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["A heuristic-assisted deep reinforcement learning algorithm for flexible job shop scheduling with transport constraints"],"prefix":"10.1007","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4835-3713","authenticated-orcid":false,"given":"Xiaoting","family":"Dong","sequence":"first","affiliation":[]},{"given":"Guangxi","family":"Wan","sequence":"additional","affiliation":[]},{"given":"Peng","family":"Zeng","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,3,17]]},"reference":[{"issue":"6","key":"1828_CR1","doi-asserted-by":"publisher","first-page":"1590","DOI":"10.1109\/TEVC.2022.3219238","volume":"27","author":"Z Pan","year":"2023","unstructured":"Pan Z, Wang L, Zheng J, Chen J-F, Wang X (2023) A learning-based multipopulation evolutionary optimization for flexible job shop scheduling problem with finite transportation resources. 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