{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T10:24:16Z","timestamp":1764584656796,"version":"3.46.0"},"reference-count":45,"publisher":"Springer Science and Business Media LLC","issue":"18","license":[{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Central Government Guided Local Science and Technology Development S\\&T Program of Hebei","award":["236Z1601G"],"award-info":[{"award-number":["236Z1601G"]}]},{"DOI":"10.13039\/501100003787","name":"Natural Science Foundation of Hebei Province","doi-asserted-by":"crossref","award":["F2022203085"],"award-info":[{"award-number":["F2022203085"]}],"id":[{"id":"10.13039\/501100003787","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["62073234"],"award-info":[{"award-number":["62073234"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Supercomput"],"DOI":"10.1007\/s11227-025-08079-9","type":"journal-article","created":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T10:19:22Z","timestamp":1764584362000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Improved whale optimization path planning design for multi-UAVs based on Pareto strategy"],"prefix":"10.1007","volume":"81","author":[{"given":"Lingyu","family":"Cheng","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fang","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chao","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,12,1]]},"reference":[{"issue":"1","key":"8079_CR1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jksuci.2023.101909","volume":"36","author":"JM Kelner","year":"2024","unstructured":"Kelner JM, Burzynski W, Stecz W (2024) Modeling uav swarm flight trajectories using rapidly-exploring random tree algorithm. J King Saud Uni-Comput Inf Sci 36(1):101909. https:\/\/doi.org\/10.1016\/j.jksuci.2023.101909","journal-title":"J King Saud Uni-Comput Inf Sci"},{"key":"8079_CR2","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.110164","volume":"260","author":"L Xu","year":"2023","unstructured":"Xu L, Cao X, Du W, Li Y (2023) Cooperative path planning optimization for multiple uavs with communication constraints. Knowl-Based Syst 260:110164. https:\/\/doi.org\/10.1016\/j.knosys.2022.110164","journal-title":"Knowl-Based Syst"},{"issue":"4","key":"8079_CR3","doi-asserted-by":"publisher","first-page":"518","DOI":"10.1007\/s11227-025-07002-6","volume":"81","author":"R Gong","year":"2025","unstructured":"Gong R, Gong H, Hong L, Li T, Xiang C (2025) A novel marine predator algorithm for path planning of uavs. J Supercomput 81(4):518. https:\/\/doi.org\/10.1007\/s11227-025-07002-6","journal-title":"J Supercomput"},{"key":"8079_CR4","doi-asserted-by":"publisher","DOI":"10.1016\/j.compeleceng.2024.109340","volume":"118","author":"H Shujuan","year":"2024","unstructured":"Shujuan H, Wenqi C, Beixuan L, Feng X, Chao S, Wenjuan Z (2024) An improved bat algorithm for collaborative dynamic target tracking and path planning of multiple uav. Comput Electr Eng 118:109340. https:\/\/doi.org\/10.1016\/j.compeleceng.2024.109340","journal-title":"Comput Electr Eng"},{"issue":"24","key":"8079_CR5","doi-asserted-by":"publisher","first-page":"13617","DOI":"10.3390\/su132413617","volume":"13","author":"CP Jayarathna","year":"2021","unstructured":"Jayarathna CP, Agdas D, Dawes L, Yigitcanlar T (2021) Multi-objective optimization for sustainable supply chain and logistics: a review. Sustainability 13(24):13617. https:\/\/doi.org\/10.3390\/su132413617","journal-title":"Sustainability"},{"key":"8079_CR6","doi-asserted-by":"publisher","first-page":"278","DOI":"10.1016\/j.ins.2022.05.123","volume":"607","author":"B Xu","year":"2022","unstructured":"Xu B, Gong D, Zhang Y, Yang S, Wang L, Fan Z, Zhang Y (2022) Cooperative co-evolutionary algorithm for multi-objective optimization problems with changing decision variables. Inf Sci 607:278\u2013296. https:\/\/doi.org\/10.1016\/j.ins.2022.05.123","journal-title":"Inf Sci"},{"issue":"1","key":"8079_CR7","doi-asserted-by":"publisher","first-page":"110","DOI":"10.1007\/s10489-009-0206-7","volume":"35","author":"T Ozyer","year":"2011","unstructured":"Ozyer T, Zhang M, Alhajj R (2011) Integrating multi-objective genetic algorithm based clustering and data partitioning for skyline computation. Appl Intell 35(1):110\u2013122. https:\/\/doi.org\/10.1007\/s10489-009-0206-7","journal-title":"Appl Intell"},{"issue":"3","key":"8079_CR8","doi-asserted-by":"publisher","first-page":"391","DOI":"10.1109\/TEVC.2018.2866927","volume":"23","author":"Q Lin","year":"2019","unstructured":"Lin Q, Liu S, Wong K-C, Gong M, Coello Coello CA, Chen J, Zhang J (2019) A clustering-based evolutionary algorithm for many-objective optimization problems. IEEE Trans Evol Comput 23(3):391\u2013405. https:\/\/doi.org\/10.1109\/TEVC.2018.2866927","journal-title":"IEEE Trans Evol Comput"},{"issue":"3","key":"8079_CR9","doi-asserted-by":"publisher","first-page":"445","DOI":"10.1109\/TEVC.2014.2339823","volume":"19","author":"M Asafuddoula","year":"2015","unstructured":"Asafuddoula M, Ray T, Sarker R (2015) A decomposition-based evolutionary algorithm for many objective optimization. IEEE Trans Evol Comput 19(3):445\u2013460. https:\/\/doi.org\/10.1109\/TEVC.2014.2339823","journal-title":"IEEE Trans Evol Comput"},{"issue":"9, SI","key":"8079_CR10","doi-asserted-by":"publisher","first-page":"2824","DOI":"10.1109\/TCYB.2016.2586191","volume":"47","author":"X Cai","year":"2017","unstructured":"Cai X, Yang Z, Fan Z, Zhang Q (2017) Decomposition-based-sorting and angle-based-selection for evolutionary multiobjective and many-objective optimization. IEEE TRANSACTIONS ON CYBERNETICS 47(9, SI):2824\u20132837. https:\/\/doi.org\/10.1109\/TCYB.2016.2586191","journal-title":"IEEE TRANSACTIONS ON CYBERNETICS"},{"key":"8079_CR11","doi-asserted-by":"publisher","DOI":"10.1016\/j.swevo.2022.101164","volume":"75","author":"P Wang","year":"2022","unstructured":"Wang P, Ma Y, Wang M (2022) A dynamic multi-objective optimization evolutionary algorithm based on particle swarm prediction strategy and prediction adjustment strategy. Swarm Evol Comput 75:101164. https:\/\/doi.org\/10.1016\/j.swevo.2022.101164","journal-title":"Swarm Evol Comput"},{"key":"8079_CR12","doi-asserted-by":"publisher","DOI":"10.1016\/j.swevo.2022.101081","volume":"72","author":"T Zhang","year":"2022","unstructured":"Zhang T, Li F, Zhao X, Qi W, Liu T (2022) A convolutional neural network-based surrogate model for multi-objective optimization evolutionary algorithm based on decomposition. Swarm Evol Comput 72:101081. https:\/\/doi.org\/10.1016\/j.swevo.2022.101081","journal-title":"Swarm Evol Comput"},{"key":"8079_CR13","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2020.106120","volume":"89","author":"R Liu","year":"2020","unstructured":"Liu R, Ren R, Liu J, Liu J (2020) A clustering and dimensionality reduction based evolutionary algorithm for large-scale multi-objective problems. Appl Soft Comput 89:106120. https:\/\/doi.org\/10.1016\/j.asoc.2020.106120","journal-title":"Appl Soft Comput"},{"key":"8079_CR14","doi-asserted-by":"publisher","unstructured":"Chen H, Zhu X, Pedrycz W, Yin S, Wu G, Yan H (2018) Pea: Parallel evolutionary algorithm by separating convergence and diversity for large-scale multi-objective optimization. In: 2018 IEEE 38TH International Conference On Distributed Computing Systems (ICDCS). IEEE International Conference on Distributed Computing Systems, pp. 223\u2013232 . https:\/\/doi.org\/10.1109\/ICDCS.2018.00031","DOI":"10.1109\/ICDCS.2018.00031"},{"key":"8079_CR15","doi-asserted-by":"publisher","first-page":"457","DOI":"10.1016\/j.ins.2018.10.007","volume":"509","author":"H Chen","year":"2020","unstructured":"Chen H, Cheng R, Wen J, Li H, Weng J (2020) Solving large-scale many-objective optimization problems by covariance matrix adaptation evolution strategy with scalable small subpopulations. Inf Sci 509:457\u2013469. https:\/\/doi.org\/10.1016\/j.ins.2018.10.007","journal-title":"Inf Sci"},{"issue":"2","key":"8079_CR16","doi-asserted-by":"publisher","first-page":"260","DOI":"10.1109\/TEVC.2017.2704782","volume":"22","author":"H Zille","year":"2018","unstructured":"Zille H, Ishibuchi H, Mostaghim S, Nojima Y (2018) A framework for large-scale multiobjective optimization based on problem transformation. IEEE Trans Evol Comput 22(2):260\u2013275. https:\/\/doi.org\/10.1109\/TEVC.2017.2704782","journal-title":"IEEE Trans Evol Comput"},{"issue":"6","key":"8079_CR17","doi-asserted-by":"publisher","first-page":"949","DOI":"10.1109\/TEVC.2019.2896002","volume":"23","author":"C He","year":"2019","unstructured":"He C, Li L, Tian Y, Zhang X, Cheng R, Jin Y, Yao X (2019) Accelerating large-scale multiobjective optimization via problem reformulation. IEEE Trans Evol Comput 23(6):949\u2013961. https:\/\/doi.org\/10.1109\/TEVC.2019.2896002","journal-title":"IEEE Trans Evol Comput"},{"key":"8079_CR18","doi-asserted-by":"crossref","unstructured":"Deb K, Gupta H (2005) Searching for robust pareto-optimal solutions in multi-objective optimization. In: Coello C, Aguirre A, Zitzler E (eds) Evolutionary multi-criterion optimization, vol 3410. Lecture Notes in Computer Science, pp 150\u2013164","DOI":"10.1007\/978-3-540-31880-4_11"},{"key":"8079_CR19","doi-asserted-by":"publisher","first-page":"864","DOI":"10.1016\/j.procs.2023.11.114","volume":"228","author":"M Li","year":"2023","unstructured":"Li M (2023) Evaluation on software performance optimization based on multi-objective optimization algorithms. Procedia Comput Sci 228:864\u2013871. https:\/\/doi.org\/10.1016\/j.procs.2023.11.114","journal-title":"Procedia Comput Sci"},{"issue":"7","key":"8079_CR20","doi-asserted-by":"publisher","first-page":"828","DOI":"10.1007\/s11227-025-07335-2","volume":"81","author":"T Xu","year":"2025","unstructured":"Xu T, Chen C, Meng F, Ma D (2025) Exponential-trigonometric optimization algorithm with multi-strategy fusion for uav three-dimensional path planning. J Supercomput 81(7):828. https:\/\/doi.org\/10.1007\/s11227-025-07335-2","journal-title":"J Supercomput"},{"issue":"2","key":"8079_CR21","doi-asserted-by":"publisher","first-page":"220","DOI":"10.1109\/TEVC.2016.2598687","volume":"21","author":"Z He","year":"2017","unstructured":"He Z, Yen GG (2017) Many-objective evolutionary algorithms based on coordinated selection strategy. IEEE Trans Evol Comput 21(2):220\u2013233. https:\/\/doi.org\/10.1109\/TEVC.2016.2598687","journal-title":"IEEE Trans Evol Comput"},{"issue":"5","key":"8079_CR22","doi-asserted-by":"publisher","first-page":"1167","DOI":"10.1109\/TEVC.2009.2021467","volume":"13","author":"A Zhou","year":"2009","unstructured":"Zhou A, Zhang Q, Jin Y (2009) Approximating the set of pareto-optimal solutions in both the decision and objective spaces by an estimation of distribution algorithm. IEEE Trans Evol Comput 13(5):1167\u20131189. https:\/\/doi.org\/10.1109\/TEVC.2009.2021467","journal-title":"IEEE Trans Evol Comput"},{"issue":"18","key":"8079_CR23","doi-asserted-by":"publisher","first-page":"26537","DOI":"10.1007\/s11227-024-06414-0","volume":"80","author":"Q Chen","year":"2024","unstructured":"Chen Q, Wang Y, Sun Y (2024) An improved dung beetle optimizer for uav 3d path planning. J Supercomput 80(18):26537\u201326567. https:\/\/doi.org\/10.1007\/s11227-024-06414-0","journal-title":"J Supercomput"},{"key":"8079_CR24","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1016\/j.advengsoft.2016.01.008","volume":"95","author":"S Mirjalili","year":"2016","unstructured":"Mirjalili S, Lewis A (2016) The whale optimization algorithm. Adv Eng Softw 95:51\u201367. https:\/\/doi.org\/10.1016\/j.advengsoft.2016.01.008","journal-title":"Adv Eng Softw"},{"key":"8079_CR25","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2023.105681","volume":"88","author":"M Chen","year":"2024","unstructured":"Chen M, Cheng Q, Feng X, Zhao K, Zhou Y, Xing B, Tang S, Wang R, Duan J, Wang J, Zhang B (2024) Optimized variational mode decomposition algorithm based on adaptive thresholding method and improved whale optimization algorithm for denoising magnetocardiography signal. Biomed Signal Process Control 88:105681. https:\/\/doi.org\/10.1016\/j.bspc.2023.105681","journal-title":"Biomed Signal Process Control"},{"key":"8079_CR26","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2023.109773","volume":"187","author":"X Wang","year":"2024","unstructured":"Wang X, Zhan L, Zhang Y, Fei T, Tseng M-L (2024) Environmental cold chain distribution center location model in the semiconductor supply chain: a hybrid arithmetic whale optimization algorithm. Comput Ind Eng 187:109773. https:\/\/doi.org\/10.1016\/j.cie.2023.109773","journal-title":"Comput Ind Eng"},{"key":"8079_CR27","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2023.128048","volume":"279","author":"S Wen","year":"2023","unstructured":"Wen S, Wang H, Qian J, Men X (2023) A novel combined model based on echo state network optimized by whale optimization algorithm for blast furnace gas prediction. Energy 279:128048. https:\/\/doi.org\/10.1016\/j.energy.2023.128048","journal-title":"Energy"},{"key":"8079_CR28","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.121862","volume":"238","author":"W Zhang","year":"2024","unstructured":"Zhang W, Peng C, Yuan Y, Cui J, Qi L (2024) A novel multi-objective evolutionary algorithm with a two-fold constraint-handling mechanism for multiple uav path planning. Expert Syst Appl 238:121862. https:\/\/doi.org\/10.1016\/j.eswa.2023.121862","journal-title":"Expert Syst Appl"},{"key":"8079_CR29","doi-asserted-by":"publisher","DOI":"10.1016\/j.compeleceng.2023.108802","volume":"110","author":"A Ait-Saadi","year":"2023","unstructured":"Ait-Saadi A, Meraihi Y, Soukane A, Yahia S, Ramdane-Cherif A, Gabis AB (2023) An enhanced African vulture optimization algorithm for solving the unmanned aerial vehicles path planning problem? Comput Electr Eng 110:108802. https:\/\/doi.org\/10.1016\/j.compeleceng.2023.108802","journal-title":"Comput Electr Eng"},{"key":"8079_CR30","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2023.111033","volume":"150","author":"K Li","year":"2024","unstructured":"Li K, Yan X, Han Y (2024) Multi-mechanism swarm optimization for multi-uav task assignment and path planning in transmission line inspection under multi-wind field. Appl Soft Comput 150:111033. https:\/\/doi.org\/10.1016\/j.asoc.2023.111033","journal-title":"Appl Soft Comput"},{"issue":"7","key":"8079_CR31","doi-asserted-by":"publisher","first-page":"100","DOI":"10.1016\/j.cja.2021.09.008","volume":"35","author":"W Zhou","year":"2022","unstructured":"Zhou W, LI J, Liu Z, Shen L (2022) Improving multi-target cooperative tracking guidance for uav swarms using multi-agent reinforcement learning. Chin J Aeronaut 35(7):100\u2013112. https:\/\/doi.org\/10.1016\/j.cja.2021.09.008","journal-title":"Chin J Aeronaut"},{"key":"8079_CR32","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2023.111108","volume":"282","author":"S Chakraborty","year":"2023","unstructured":"Chakraborty S, Saha AK, Ezugwu AE, Chakraborty R, Saha A (2023) Horizontal crossover and co-operative hunting-based whale optimization algorithm for feature selection. Knowl-Based Syst 282:111108. https:\/\/doi.org\/10.1016\/j.knosys.2023.111108","journal-title":"Knowl-Based Syst"},{"key":"8079_CR33","doi-asserted-by":"publisher","DOI":"10.1016\/j.memori.2023.100086","volume":"6","author":"MW Hasan","year":"2023","unstructured":"Hasan MW (2023) Building an IOT temperature and humidity forecasting model based on long short-term memory (lstm) with improved whale optimization algorithm. Mem - Mater Devices Circuits Syst 6:100086. https:\/\/doi.org\/10.1016\/j.memori.2023.100086","journal-title":"Mem - Mater Devices Circuits Syst"},{"key":"8079_CR34","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2023.110554","volume":"144","author":"H Zhang","year":"2023","unstructured":"Zhang H, Gao Z, Pan Y, Yang G, Zhang WJC, Wang J (2023) A synergy of the adaptive whale optimization algorithm and differential evolution for abrupt motion tracking. Appl Soft Comput 144:110554. https:\/\/doi.org\/10.1016\/j.asoc.2023.110554","journal-title":"Appl Soft Comput"},{"key":"8079_CR35","doi-asserted-by":"publisher","DOI":"10.1016\/j.compstruct.2023.116764","volume":"310","author":"W Wang","year":"2023","unstructured":"Wang W, Wang Q, Zhong R, Chen L, Shi X (2023) Stacking sequence optimization of arbitrary quadrilateral laminated plates for maximum fundamental frequency by hybrid whale optimization algorithm. Compos Struct 310:116764. https:\/\/doi.org\/10.1016\/j.compstruct.2023.116764","journal-title":"Compos Struct"},{"key":"8079_CR36","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2021.104558","volume":"108","author":"W Yang","year":"2022","unstructured":"Yang W, Xia K, Fan S, Wang L, Li T, Zhang J, Feng Y (2022) A multi-strategy whale optimization algorithm and its application. Eng Appl Artif Intell 108:104558. https:\/\/doi.org\/10.1016\/j.engappai.2021.104558","journal-title":"Eng Appl Artif Intell"},{"key":"8079_CR37","doi-asserted-by":"publisher","first-page":"90165","DOI":"10.1109\/ACCESS.2020.2993580","volume":"8","author":"X Chen","year":"2020","unstructured":"Chen X (2020) Research on new adaptive whale algorithm. IEEE Access 8:90165\u201390201. https:\/\/doi.org\/10.1109\/ACCESS.2020.2993580","journal-title":"IEEE Access"},{"issue":"14","key":"8079_CR38","doi-asserted-by":"publisher","first-page":"4821","DOI":"10.3390\/app10144821","volume":"10","author":"Y Zhang","year":"2020","unstructured":"Zhang Y, Wang P, Yang L, Liu Y, Lu Y, Zhu X (2020) Novel swarm intelligence algorithm for global optimization and multi-uavs cooperative path planning: Anas platyrhynchos optimizer. Appl Sci-Basel 10(14):4821. https:\/\/doi.org\/10.3390\/app10144821","journal-title":"Appl Sci-Basel"},{"key":"8079_CR39","doi-asserted-by":"publisher","first-page":"878","DOI":"10.1016\/j.neucom.2015.07.044","volume":"171","author":"Y Chen","year":"2016","unstructured":"Chen Y, Yu J, Mei Y, Wang Y, Su X (2016) Modified central force optimization (mcfo) algorithm for 3d uav path planning. Neurocomputing 171:878\u2013888. https:\/\/doi.org\/10.1016\/j.neucom.2015.07.044","journal-title":"Neurocomputing"},{"issue":"2","key":"8079_CR40","doi-asserted-by":"publisher","first-page":"529","DOI":"10.1109\/JAS.2023.123945","volume":"11","author":"S Feng","year":"2024","unstructured":"Feng S, Zeng L, Liu J, Yang Y, Song W (2024) Multi-uavs collaborative path planning in the cramped environment. IEEE-CAA J Autom Sin 11(2):529\u2013538. https:\/\/doi.org\/10.1109\/JAS.2023.123945","journal-title":"IEEE-CAA J Autom Sin"},{"issue":"6","key":"8079_CR41","doi-asserted-by":"publisher","first-page":"712","DOI":"10.1109\/TEVC.2007.892759","volume":"11","author":"Q Zhang","year":"2007","unstructured":"Zhang Q, Li H (2007) Moea\/d: a multiobjective evolutionary algorithm based on decomposition. IEEE Trans Evol Comput 11(6):712\u2013731. https:\/\/doi.org\/10.1109\/TEVC.2007.892759","journal-title":"IEEE Trans Evol Comput"},{"issue":"2","key":"8079_CR42","doi-asserted-by":"publisher","first-page":"182","DOI":"10.1109\/4235.996017","volume":"6","author":"K Deb","year":"2002","unstructured":"Deb K, Pratap A, Agarwal S, Meyarivan T (2002) A fast and elitist multiobjective genetic algorithm: Nsga-ii. IEEE Trans Evol Comput 6(2):182\u2013197. https:\/\/doi.org\/10.1109\/4235.996017","journal-title":"IEEE Trans Evol Comput"},{"issue":"4","key":"8079_CR43","doi-asserted-by":"publisher","first-page":"577","DOI":"10.1109\/TEVC.2013.2281535","volume":"18","author":"K Deb","year":"2014","unstructured":"Deb K, Jain H (2014) An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, part i: Solving problems with box constraints. IEEE Trans Evol Comput 18(4):577\u2013601. https:\/\/doi.org\/10.1109\/TEVC.2013.2281535","journal-title":"IEEE Trans Evol Comput"},{"key":"8079_CR44","doi-asserted-by":"publisher","unstructured":"Khodadadi N, El-kenawy E-SM, Faridmarandi S, Ghahfarokhi MS, Ibrahim A, Mirjalili S (2024) Chapter 42 - a novel version of whale optimization algorithm for solving optimization problems. In: Mirjalili, S (ed) Handbook of Whale Optimization Algorithm, pp 591\u2013600 . https:\/\/doi.org\/10.1016\/B978-0-32-395365-8.00048-8","DOI":"10.1016\/B978-0-32-395365-8.00048-8"},{"key":"8079_CR45","doi-asserted-by":"publisher","unstructured":"Hohmann N, Bujny M, Adamy J, Olhofer M, (2022) Multi-objective 3d path planning for uavs in large-scale urban scenarios. In: (2022) IEEE Congress on Evolutionary Computation. https:\/\/doi.org\/10.1109\/CEC55065.2022.9870265","DOI":"10.1109\/CEC55065.2022.9870265"}],"container-title":["The Journal of Supercomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-025-08079-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11227-025-08079-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-025-08079-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T10:19:24Z","timestamp":1764584364000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11227-025-08079-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,1]]},"references-count":45,"journal-issue":{"issue":"18","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["8079"],"URL":"https:\/\/doi.org\/10.1007\/s11227-025-08079-9","relation":{},"ISSN":["1573-0484"],"issn-type":[{"value":"1573-0484","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,1]]},"assertion":[{"value":"15 September 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 November 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 December 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"1615"}}