{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T15:01:11Z","timestamp":1785510071783,"version":"3.56.0"},"reference-count":30,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Computers &amp; Operations Research"],"published-print":{"date-parts":[[2025,5]]},"DOI":"10.1016\/j.cor.2025.106993","type":"journal-article","created":{"date-parts":[[2025,1,31]],"date-time":"2025-01-31T18:18:12Z","timestamp":1738347492000},"page":"106993","update-policy":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":32,"special_numbering":"C","title":["Improved A* algorithm incorporating RRT* thought: A path planning algorithm for AGV in digitalised workshops"],"prefix":"10.1016","volume":"177","author":[{"given":"Na","family":"Liu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0009-0001-8627-2001","authenticated-orcid":false,"given":"Zihang","family":"Hu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Min","family":"Wei","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0009-0009-2409-4690","authenticated-orcid":false,"given":"Pengfei","family":"Guo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuhan","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aodi","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"4","key":"10.1016\/j.cor.2025.106993_b0005","doi-asserted-by":"crossref","first-page":"341","DOI":"10.3844\/jcssp.2008.341.344","article-title":"A mobile robot path planning using genetic algorithm in static environment","volume":"4","author":"Al-Taharwa","year":"2008","journal-title":"J. Comput. Sci."},{"key":"10.1016\/j.cor.2025.106993_b0010","doi-asserted-by":"crossref","DOI":"10.1016\/j.oceaneng.2023.113965","article-title":"USV path planning algorithm based on plant growth","volume":"273","author":"Bai","year":"2023","journal-title":"Ocean Eng."},{"issue":"2","key":"10.1016\/j.cor.2025.106993_b0015","doi-asserted-by":"crossref","first-page":"590","DOI":"10.1016\/j.ejor.2022.10.023","article-title":"The parallel AGV scheduling problem with battery constraints: a new formulation and a matheuristic approach","volume":"307","author":"Boccia","year":"2023","journal-title":"Eur. J. Oper. Res."},{"key":"10.1016\/j.cor.2025.106993_b0020","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1016\/j.procir.2023.06.020","article-title":"Smart maintenance architecture for automated guided vehicles","volume":"118","author":"Bozhdaraj","year":"2023","journal-title":"Procedia CIRP"},{"key":"10.1016\/j.cor.2025.106993_b0025","doi-asserted-by":"crossref","first-page":"604","DOI":"10.1016\/j.procs.2014.05.466","article-title":"On the adequacy of Tabu search for global robot path planning problem in grid environments","volume":"32","author":"Ch\u00e2ari","year":"2014","journal-title":"Procedia Comp. Sci."},{"key":"10.1016\/j.cor.2025.106993_b0030","doi-asserted-by":"crossref","DOI":"10.1016\/j.cor.2021.105517","article-title":"Scheduling heterogeneous multi-load AGVs with battery constraints","volume":"136","author":"Dang","year":"2021","journal-title":"Comp. Oper. Res."},{"key":"10.1016\/j.cor.2025.106993_b0035","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1016\/j.jmsy.2021.11.012","article-title":"Decentral task allocation for industrial AGV-systems with routing constraints","volume":"62","author":"De Ryck","year":"2022","journal-title":"J. Manuf. Syst."},{"key":"10.1016\/j.cor.2025.106993_b0040","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1016\/j.robot.2018.04.007","article-title":"An improved A* algorithm for the industrial robot path planning with high success rate and short length","volume":"106","author":"Fu","year":"2018","journal-title":"Robot. Autonomous Syst."},{"issue":"1","key":"10.1016\/j.cor.2025.106993_b0045","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.jmsy.2009.06.001","article-title":"The performance of load-selection rules and pickup-dispatching rules for multiple-load AGVs","volume":"28","author":"Ho","year":"2009","journal-title":"J. Manuf. Syst."},{"key":"10.1016\/j.cor.2025.106993_b0050","article-title":"Conflict-free scheduling of large-scale multi-load AGVs in material transportation network, Transport","volume":"158","author":"Hu","year":"2022","journal-title":"Res. Part E: Log. Transport. Rev."},{"key":"10.1016\/j.cor.2025.106993_b0055","doi-asserted-by":"crossref","DOI":"10.1016\/j.ijpe.2023.108913","article-title":"The impact of industry 4.0 on supply chain capability and supply chain resilience: a dynamic resource-based view","volume":"262","author":"Huang","year":"2023","journal-title":"Int. J. Product. Econ."},{"issue":"7","key":"10.1016\/j.cor.2025.106993_b0060","doi-asserted-by":"crossref","first-page":"846","DOI":"10.1177\/0278364911406761","article-title":"Sampling-based algorithms for optimal motion planning","volume":"30","author":"Karaman","year":"2011","journal-title":"Int. J. Robotics Res."},{"key":"10.1016\/j.cor.2025.106993_b0065","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2021.108084","article-title":"A hybrid approach for forecasting ship motion using CNN\u2013GRU\u2013AM and GCWOA","volume":"114","author":"Li","year":"2022","journal-title":"Appl. Soft Comput."},{"key":"10.1016\/j.cor.2025.106993_b0070","doi-asserted-by":"crossref","DOI":"10.1016\/j.cie.2022.108123","article-title":"Global path planning based on a bidirectional alternating search A* algorithm for mobile robots","volume":"168","author":"Li","year":"2022","journal-title":"Comp. Ind. Eng."},{"key":"10.1016\/j.cor.2025.106993_b0075","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2020.113425","article-title":"PQ-RRT*: An improved path planning algorithm for mobile robots","volume":"152","author":"Li","year":"2020","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.cor.2025.106993_b0080","doi-asserted-by":"crossref","DOI":"10.1016\/j.oceaneng.2023.114610","article-title":"Three-dimensional path planning for AUVs in ocean currents environment based on an improved compression factor particle swarm optimization algorithm","volume":"280","author":"Li","year":"2023","journal-title":"Ocean Eng."},{"issue":"12","key":"10.1016\/j.cor.2025.106993_b0085","doi-asserted-by":"crossref","first-page":"497","DOI":"10.1016\/j.ifacol.2016.07.669","article-title":"Decentralized management of intersections of automated guided vehicles","volume":"49","author":"Lombard","year":"2016","journal-title":"IFAC-PapersOnLine"},{"key":"10.1016\/j.cor.2025.106993_b0090","doi-asserted-by":"crossref","first-page":"1555","DOI":"10.1007\/s00521-019-04172-2","article-title":"Research on path planning of mobile robot based on improved ant colony algorithm","volume":"32","author":"Luo","year":"2020","journal-title":"Neural Comp. Appl."},{"key":"10.1016\/j.cor.2025.106993_b0095","doi-asserted-by":"crossref","DOI":"10.1016\/j.compind.2022.103797","article-title":"Hybrid supervisory-based architecture for robust control of Bi-directional AGVs","volume":"144","author":"Maza","year":"2023","journal-title":"Comp. Ind."},{"key":"10.1016\/j.cor.2025.106993_b0100","doi-asserted-by":"crossref","first-page":"130","DOI":"10.1016\/j.jmsy.2023.03.007","article-title":"A novel multi-tasks chain scheduling algorithm based on capacity prediction to solve AGV dispatching problem in an intelligent manufacturing system","volume":"68","author":"Niu","year":"2023","journal-title":"J. Manuf. Syst."},{"issue":"8","key":"10.1016\/j.cor.2025.106993_b0105","doi-asserted-by":"crossref","first-page":"7244","DOI":"10.1109\/TIE.2020.2998740","article-title":"MOD-RRT*: a sampling-based algorithm for robot path planning in dynamic environment","volume":"68","author":"Qi","year":"2021","journal-title":"IEEE Trans. Ind. Electron."},{"key":"10.1016\/j.cor.2025.106993_b0110","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/j.apor.2018.12.001","article-title":"Smoothed A* algorithm for practical unmanned surface vehicle path planning","volume":"83","author":"Song","year":"2019","journal-title":"Appl. Ocean Res."},{"key":"10.1016\/j.cor.2025.106993_b0115","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2022.101755","article-title":"A hybrid formation path planning based on A* and multi-target improved artificial potential field algorithm in the 2D random environments","volume":"54","author":"Tong","year":"2022","journal-title":"Adv. Eng. Inf."},{"issue":"3","key":"10.1016\/j.cor.2025.106993_b0120","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1016\/j.vrih.2022.11.002","article-title":"Research on AGV task path planning based on improved A* algorithm","volume":"5","author":"Xianwei","year":"2023","journal-title":"Virtual Reality Intell. Hardware"},{"key":"10.1016\/j.cor.2025.106993_b0125","doi-asserted-by":"crossref","unstructured":"Yafei, L., W. Anping, C. Qingyang, W. Yujie, An improved UAV path planning method based on RRT-APF hybrid strategy, in: 2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE), Dalian, China, 2020, pp. 81-86, doi: 10.1109\/CACRE50138.2020.9229999.","DOI":"10.1109\/CACRE50138.2020.9229999"},{"key":"10.1016\/j.cor.2025.106993_b0130","doi-asserted-by":"crossref","first-page":"482","DOI":"10.1016\/j.cie.2018.10.007","article-title":"Octavian Postolache, An integrated scheduling method for AGV routing in automated container terminals","volume":"126","author":"Yang","year":"2018","journal-title":"Comp. Ind. Eng."},{"issue":"Part 3","key":"10.1016\/j.cor.2025.106993_b0135","article-title":"Path planning of unmanned surface vessel in an unknown environment based on improved D*Lite algorithm","volume":"266","author":"Yu","year":"2022","journal-title":"Ocean Eng."},{"key":"10.1016\/j.cor.2025.106993_b0140","doi-asserted-by":"crossref","DOI":"10.1016\/j.cie.2020.106371","article-title":"Multi-AGV scheduling for conflict-free path planning in automated container terminals","volume":"142","author":"Zhong","year":"2020","journal-title":"Comp. Ind. Eng."},{"key":"10.1016\/j.cor.2025.106993_b0145","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2021.101376","article-title":"Lifting path planning of mobile cranes based on an improved RRT algorithm","volume":"50","author":"Zhou","year":"2021","journal-title":"Adv. Eng. Inf."},{"key":"10.1016\/j.cor.2025.106993_b0150","doi-asserted-by":"crossref","unstructured":"Zhu, Z., Xie, J., Wang, Z., Global dynamic path planning based on fusion of A* algorithm and dynamic window approach, 2019 Chinese Automation Congress (CAC), Hangzhou, China, 2019, pp. 5572-5576, doi: 10.1109\/CAC48633.2019.8996741.","DOI":"10.1109\/CAC48633.2019.8996741"}],"container-title":["Computers &amp; Operations Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/api.elsevier.com\/content\/article\/PII:S0305054825000218?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/api.elsevier.com\/content\/article\/PII:S0305054825000218?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,2,25]],"date-time":"2025-02-25T12:56:55Z","timestamp":1740488215000},"score":1,"resource":{"primary":{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/linkinghub.elsevier.com\/retrieve\/pii\/S0305054825000218"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5]]},"references-count":30,"alternative-id":["S0305054825000218"],"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1016\/j.cor.2025.106993","relation":{},"ISSN":["0305-0548"],"issn-type":[{"value":"0305-0548","type":"print"}],"subject":[],"published":{"date-parts":[[2025,5]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Improved A* algorithm incorporating RRT* thought: A path planning algorithm for AGV in digitalised workshops","name":"articletitle","label":"Article Title"},{"value":"Computers & Operations Research","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1016\/j.cor.2025.106993","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"106993"}}