{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T16:11:05Z","timestamp":1772727065238,"version":"3.50.1"},"publisher-location":"Cham","reference-count":18,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031378713","type":"print"},{"value":"9783031378720","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-3-031-37872-0_9","type":"book-chapter","created":{"date-parts":[[2023,7,11]],"date-time":"2023-07-11T23:02:16Z","timestamp":1689116536000},"page":"117-133","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["A Hybrid Approach of\u00a0Dijkstra\u2019s Algorithm and\u00a0A* Search, with\u00a0an\u00a0Optional Adaptive Threshold Heuristic"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-6477-4416","authenticated-orcid":false,"given":"Lhoussaine","family":"Ait Ben Mouh","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1615-367X","authenticated-orcid":false,"given":"Mohamed","family":"Ouhda","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7851-3816","authenticated-orcid":false,"given":"Youssef","family":"El Mourabit","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4819-533X","authenticated-orcid":false,"given":"Mohamed","family":"Baslam","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,7,12]]},"reference":[{"key":"9_CR1","doi-asserted-by":"publisher","first-page":"4149","DOI":"10.1007\/s00500-015-1750-1","volume":"20","author":"A Ammar","year":"2016","unstructured":"Ammar, A., Bennaceur, H., Ch\u00e2ari, I., Koub\u00e2a, A., Alajlan, M.: Relaxed Dijkstra and A* with linear complexity for robot path planning problems in large-scale grid environments. Soft. Comput. 20, 4149\u20134171 (2016)","journal-title":"Soft. Comput."},{"key":"9_CR2","doi-asserted-by":"publisher","first-page":"1025","DOI":"10.1007\/s10851-018-0793-1","volume":"60","author":"KC Ciesielski","year":"2018","unstructured":"Ciesielski, K.C., Falc\u00e3o, A.X., Miranda, P.A.: Path-value functions for which Dijkstra\u2019s algorithm returns optimal mapping. J. Math. Imaging Vision 60, 1025\u20131036 (2018)","journal-title":"J. Math. Imaging Vision"},{"key":"9_CR3","doi-asserted-by":"crossref","unstructured":"Ferguson, D., Kalra, N., Stentz, A.: Replanning with RRTs. In: Proceedings 2006 IEEE International Conference on Robotics and Automation, ICRA 2006, pp. 1243\u20131248. IEEE (2006)","DOI":"10.1109\/ROBOT.2006.1641879"},{"key":"9_CR4","doi-asserted-by":"crossref","unstructured":"Fernandes, P.B., Oliveira, RCL., Neto, J.F.: Trajectory planning of autonomous mobile robots applying a particle swarm optimization algorithm with peaks of diversity. Appl. Soft Comput. 116, 108108 (2022)","DOI":"10.1016\/j.asoc.2021.108108"},{"key":"9_CR5","doi-asserted-by":"crossref","unstructured":"Ju, C., Luo, Q., Yan, X.: Path planning using an improved A-star algorithm. In: 2020 11th International Conference on Prognostics and System Health Management (PHM-2020 Jinan), pp. 23\u201326. IEEE (2020)","DOI":"10.1109\/PHM-Jinan48558.2020.00012"},{"issue":"1","key":"9_CR6","doi-asserted-by":"publisher","first-page":"90","DOI":"10.1177\/027836498600500106","volume":"5","author":"O Khatib","year":"1986","unstructured":"Khatib, O.: Real-time obstacle avoidance for manipulators and mobile robots. Int. J. Robot. Res. 5(1), 90\u201398 (1986)","journal-title":"Int. J. Robot. Res."},{"key":"9_CR7","doi-asserted-by":"publisher","DOI":"10.1016\/j.compag.2021.106350","volume":"188","author":"G Lin","year":"2021","unstructured":"Lin, G., Zhu, L., Li, J., Zou, X., Tang, Y.: Collision-free path planning for a guava-harvesting robot based on recurrent deep reinforcement learning. Comput. Electron. Agric. 188, 106350 (2021)","journal-title":"Comput. Electron. Agric."},{"key":"9_CR8","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.114660","volume":"173","author":"\u00c1 Madridano","year":"2021","unstructured":"Madridano, \u00c1., Al-Kaff, A., Mart\u00edn, D., de la Escalera, A.: Trajectory planning for multi-robot systems: methods and applications. Expert Syst. Appl. 173, 114660 (2021)","journal-title":"Expert Syst. Appl."},{"key":"9_CR9","doi-asserted-by":"publisher","first-page":"425","DOI":"10.1007\/s10846-017-0748-6","volume":"91","author":"A Niewola","year":"2018","unstructured":"Niewola, A., Podsedkowski, L.: L* algorithm-a linear computational complexity graph searching algorithm for path planning. J. Intell. Robot. Syst. 91, 425\u2013444 (2018)","journal-title":"J. Intell. Robot. Syst."},{"key":"9_CR10","doi-asserted-by":"publisher","first-page":"60253","DOI":"10.1109\/ACCESS.2022.3181131","volume":"10","author":"J Pak","year":"2022","unstructured":"Pak, J., Kim, J., Park, Y., Son, H.I.: Field evaluation of path-planning algorithms for autonomous mobile robot in smart farms. IEEE Access 10, 60253\u201360266 (2022)","journal-title":"IEEE Access"},{"issue":"1","key":"9_CR11","doi-asserted-by":"publisher","first-page":"753","DOI":"10.1109\/TVT.2021.3125401","volume":"71","author":"A Ranjha","year":"2021","unstructured":"Ranjha, A., Kaddoum, G.: URLLC-enabled by laser powered UAV relay: a quasi-optimal design of resource allocation, trajectory planning and energy harvesting. IEEE Trans. Veh. Technol. 71(1), 753\u2013765 (2021)","journal-title":"IEEE Trans. Veh. Technol."},{"issue":"1","key":"9_CR12","first-page":"152","volume":"7","author":"K Sandamurthy","year":"2020","unstructured":"Sandamurthy, K., Ramanujam, K.: A hybrid weed optimized coverage path planning technique for autonomous harvesting in cashew orchards. Inf. Process. Agric. 7(1), 152\u2013164 (2020)","journal-title":"Inf. Process. Agric."},{"issue":"17","key":"9_CR13","doi-asserted-by":"publisher","first-page":"1770","DOI":"10.1364\/OL.20.001770","volume":"20","author":"AJ Stentz","year":"1995","unstructured":"Stentz, A.J., Boyd, R.W., Evans, A.F.: Dramatically improved transmission of ultrashort solitons through 40 km of dispersion-decreasing fiber. Opt. Lett. 20(17), 1770\u20131772 (1995)","journal-title":"Opt. Lett."},{"key":"9_CR14","unstructured":"Thrasher, S.W.: A reactive\/deliberative planner using genetic algorithms on tactical primitives. Ph.D. thesis, Massachusetts Institute of Technology (2006)"},{"issue":"4","key":"9_CR15","doi-asserted-by":"publisher","first-page":"531","DOI":"10.1080\/13658810801949850","volume":"23","author":"W Zeng","year":"2009","unstructured":"Zeng, W., Church, R.L.: Finding shortest paths on real road networks: the case for A*. Int. J. Geogr. Inf. Sci. 23(4), 531\u2013543 (2009). https:\/\/doi.org\/10.1080\/13658810801949850","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"9_CR16","doi-asserted-by":"publisher","unstructured":"Zhang, H.Y., Lin, W.M., Chen, A.X.: Path planning for the mobile robot: a review. Symmetry 10(10), 450 (2018). https:\/\/doi.org\/10.3390\/sym10100450","DOI":"10.3390\/sym10100450"},{"issue":"3","key":"9_CR17","doi-asserted-by":"publisher","first-page":"4158","DOI":"10.1007\/s11227-021-04031-9","volume":"78","author":"TW Zhang","year":"2022","unstructured":"Zhang, T.W., Xu, G.H., Zhan, X.S., Han, T.: A new hybrid algorithm for path planning of mobile robot. J. Supercomput. 78(3), 4158\u20134181 (2022)","journal-title":"J. Supercomput."},{"key":"9_CR18","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1007\/s10846-019-01112-z","volume":"99","author":"X Zhong","year":"2020","unstructured":"Zhong, X., Tian, J., Hu, H., Peng, X.: Hybrid path planning based on safe A* algorithm and adaptive window approach for mobile robot in large-scale dynamic environment. J. Intell. Robot. Syst. 99, 65\u201377 (2020)","journal-title":"J. Intell. Robot. Syst."}],"container-title":["Lecture Notes in Business Information Processing","Business Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-37872-0_9","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,24]],"date-time":"2024-10-24T00:00:30Z","timestamp":1729728030000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-37872-0_9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031378713","9783031378720"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-37872-0_9","relation":{},"ISSN":["1865-1348","1865-1356"],"issn-type":[{"value":"1865-1348","type":"print"},{"value":"1865-1356","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"12 July 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CBI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Business Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Istanbul","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"T\u00fcrkiye","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 July 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21 July 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"cbi2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.cbibm.com\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"50","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"15","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"30% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}