{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T09:45:47Z","timestamp":1772531147756,"version":"3.50.1"},"publisher-location":"Singapore","reference-count":20,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819771806","type":"print"},{"value":"9789819771813","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[[2024]]},"DOI":"10.1007\/978-981-97-7181-3_36","type":"book-chapter","created":{"date-parts":[[2024,8,22]],"date-time":"2024-08-22T08:37:21Z","timestamp":1724315841000},"page":"451-462","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Multi-objective Path Planning of Multiple Unmanned Air Vehicles Using the CCMO Algorithm"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-2077-5172","authenticated-orcid":false,"given":"Zhenghan","family":"Zhou","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0003-0033-9493","authenticated-orcid":false,"given":"Yutong","family":"Liu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3533-7204","authenticated-orcid":false,"given":"Tianwei","family":"Zhou","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5822-8743","authenticated-orcid":false,"given":"Ben","family":"Niu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,8,21]]},"reference":[{"key":"36_CR1","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1016\/j.knosys.2018.05.033","volume":"158","author":"Y Zhao","year":"2018","unstructured":"Zhao, Y., Zheng, Z., Liu, Y.: Survey on computational-intelligence-based UAV path planning. Knowl.-Based Syst. 158, 54\u201364 (2018)","journal-title":"Knowl.-Based Syst."},{"issue":"1","key":"36_CR2","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1109\/MWC.2018.1800160","volume":"26","author":"N Zhao","year":"2019","unstructured":"Zhao, N., et al.: UAV-assisted emergency networks in disasters. IEEE Wirel. Commun. 26(1), 45\u201351 (2019)","journal-title":"IEEE Wirel. Commun."},{"key":"36_CR3","doi-asserted-by":"crossref","unstructured":"Mancini, A., Frontoni, E., Zingaretti, P.: Satellite and UAV data for precision agriculture applications. In\u00a02019 International Conference on Unmanned Aircraft Systems, ICUAS,\u00a0pp. 491\u2013497. IEEE (2019)","DOI":"10.1109\/ICUAS.2019.8797930"},{"key":"36_CR4","doi-asserted-by":"publisher","first-page":"12395","DOI":"10.1109\/ACCESS.2018.2804899","volume":"6","author":"P Razi","year":"2018","unstructured":"Razi, P., Sumantyo, J.T.S., Perissin, D., Kuze, H., Chua, M.Y., Panggabean, G.F.: 3D land mapping and land deformation monitoring using persistent scatterer interferometry (PSI) ALOS PALSAR: Validated by Geodetic GPS and UAV. IEEE Access 6, 12395\u201312404 (2018)","journal-title":"IEEE Access"},{"issue":"3","key":"36_CR5","doi-asserted-by":"publisher","first-page":"1698","DOI":"10.1109\/JIOT.2018.2796243","volume":"5","author":"P Kumar","year":"2018","unstructured":"Kumar, P., Garg, S., Singh, A., Batra, S., Kumar, N., You, I.: MVO-based 2-D path planning scheme for providing quality of service in UAV environment. IEEE Internet Things J. 5(3), 1698\u20131707 (2018)","journal-title":"IEEE Internet Things J."},{"issue":"5","key":"36_CR6","doi-asserted-by":"publisher","first-page":"1151","DOI":"10.23919\/JSEE.2022.000111","volume":"33","author":"H Zhang","year":"2022","unstructured":"Zhang, H., Gan, X., Li, S., Chen, Z.: UAV safe route planning based on PSO-BAS algorithm. J. Syst. Eng. Electron. 33(5), 1151\u20131160 (2022)","journal-title":"J. Syst. Eng. Electron."},{"key":"36_CR7","doi-asserted-by":"crossref","unstructured":"Basbous, B.: 2D UAV path planning with radar threatening areas using simulated annealing algorithm for event detection. In: 2018 International Conference on Artificial Intelligence and Data Processing IDAP, pp. 1\u20137. IEEE (2018)","DOI":"10.1109\/IDAP.2018.8620881"},{"key":"36_CR8","doi-asserted-by":"publisher","first-page":"109075","DOI":"10.1016\/j.knosys.2022.109075","volume":"250","author":"X Zhang","year":"2022","unstructured":"Zhang, X., Xia, S., Li, X., Zhang, T.: Multi-objective particle swarm optimization with multi-mode collaboration based on reinforcement learning for path planning of unmanned air vehicles. Knowl.-Based Syst. 250, 109075 (2022)","journal-title":"Knowl.-Based Syst."},{"key":"36_CR9","doi-asserted-by":"crossref","unstructured":"Yershov, D.S., LaValle, S.M.: Simplicial Dijkstra and A* algorithms for optimal feedback planning. In: 2011 IEEE\/RSJ International Conference on Intelligent Robots and Systems, IROS, pp. 3862\u20133867. IEEE (2011)","DOI":"10.1109\/IROS.2011.6048681"},{"issue":"2","key":"36_CR10","doi-asserted-by":"publisher","first-page":"100","DOI":"10.1109\/TSSC.1968.300136","volume":"4","author":"PE Hart","year":"1968","unstructured":"Hart, P.E., Nilsson, N.J., Raphael, B.: A formal basis for the heuristic determination of minimum cost paths. IEEE Trans. Syst. Sci. Cybern. 4(2), 100\u2013107 (1968)","journal-title":"IEEE Trans. Syst. Sci. Cybern."},{"key":"36_CR11","doi-asserted-by":"crossref","unstructured":"Karaboga, D., Akay, B.: Artificial bee colony (ABC) algorithm on training artificial neural networks. In: IEEE 15th Signal Processing and Communications Applications, SIU, pp. 1\u22124. IEEE (2007)","DOI":"10.1109\/SIU.2007.4298679"},{"issue":"11","key":"36_CR12","doi-asserted-by":"publisher","first-page":"6784","DOI":"10.1109\/TITS.2020.2994779","volume":"22","author":"SZ Zhou","year":"2020","unstructured":"Zhou, S.Z., Zhan, Z.H., Chen, Z.G., Kwong, S., Zhang, J.: A multi-objective ant colony system algorithm for airline crew rostering problem with fairness and satisfaction. IEEE Trans. Intell. Transp. Syst. 22(11), 6784\u20136798 (2020)","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"36_CR13","doi-asserted-by":"crossref","unstructured":"Kennedy, J., Eberhart, R.: Particle swarm optimization. In Proceedings of International Conference on Neural Networks, ICNN\u201995, vol. 4, pp. 1942\u20131948. IEEE (1995)","DOI":"10.1109\/ICNN.1995.488968"},{"issue":"1\u20132","key":"36_CR14","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/S0304-3975(00)00406-0","volume":"259","author":"LM Schmitt","year":"2001","unstructured":"Schmitt, L.M.: Theory of genetic algorithms. Theoret. Comput. Sci. 259(1\u20132), 1\u201361 (2001)","journal-title":"Theoret. Comput. Sci."},{"key":"36_CR15","doi-asserted-by":"publisher","first-page":"341","DOI":"10.1023\/A:1008202821328","volume":"11","author":"R Storn","year":"1997","unstructured":"Storn, R., Price, K.: Differential evolution\u2013a simple and efficient heuristic for global optimization over continuous spaces. J. Global Optim. 11, 341\u2013359 (1997)","journal-title":"J. Global Optim."},{"issue":"1","key":"36_CR16","doi-asserted-by":"publisher","first-page":"102","DOI":"10.1109\/TEVC.2020.3004012","volume":"25","author":"Y Tian","year":"2020","unstructured":"Tian, Y., Zhang, T., Xiao, J., Zhang, X., Jin, Y.: A coevolutionary framework for constrained multiobjective optimization problems. IEEE Trans. Evol. Comput. 25(1), 102\u2013116 (2020)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"36_CR17","doi-asserted-by":"publisher","unstructured":"Deb, K., Agrawal, S., Pratap, A., Meyarivan, T.: A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II. In: Schoenauer, M., et al. Parallel Problem Solving from Nature PPSN VI. PPSN 2000. Lecture Notes in Computer Science, vol. 19107, pp. 849\u2013858. Springer, Berlin, Heidelberg (2000). https:\/\/doi.org\/10.1007\/3-540-45356-3_83","DOI":"10.1007\/3-540-45356-3_83"},{"key":"36_CR18","doi-asserted-by":"publisher","first-page":"109075","DOI":"10.1016\/j.knosys.2022.109075","volume":"250","author":"X Zhang","year":"2022","unstructured":"Zhang, X., Xia, S., Li, X., et al.: Multi-objective particle swarm optimization with multi-mode collaboration based on reinforcement learning for path planning of unmanned air vehicles. Knowl.-Based Syst. 250, 109075 (2022)","journal-title":"Knowl.-Based Syst."},{"issue":"10","key":"36_CR19","doi-asserted-by":"publisher","first-page":"6222","DOI":"10.1109\/TSMC.2022.3143657","volume":"52","author":"F Ming","year":"2022","unstructured":"Ming, F., Gong, W., Wang, L.: A two-stage evolutionary algorithm with balanced convergence and diversity for many-objective optimization. IEEE Trans. Syst. Man Cybern. Syst. 52(10), 6222\u20136234 (2022)","journal-title":"IEEE Trans. Syst. Man Cybern. Syst."},{"key":"36_CR20","doi-asserted-by":"crossref","unstructured":"Coello, C.C., Lechuga, M.S.: MOPSO: A proposal for multiple objective particle swarm optimization. In: Proceedings of the 2002 Congress on Evolutionary Computation CEC\u201902. Honolulu, HI, USA, vol. 2, pp. 1051\u20131056. IEEE (2002)","DOI":"10.1109\/CEC.2002.1004388"}],"container-title":["Lecture Notes in Computer Science","Advances in Swarm Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-97-7181-3_36","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,22]],"date-time":"2024-08-22T09:13:22Z","timestamp":1724318002000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-97-7181-3_36"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9789819771806","9789819771813"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-981-97-7181-3_36","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"21 August 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICSI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Swarm Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Xining","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 August 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 August 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"swarm2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.iasei.org\/icsi2024\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}