{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T14:58:24Z","timestamp":1787669904273,"version":"build-2736575974"},"reference-count":47,"publisher":"Springer Science and Business Media LLC","issue":"11","license":[{"start":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T00:00:00Z","timestamp":1757548800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T00:00:00Z","timestamp":1757548800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"JSPS KAKENHI","award":["24K15098"],"award-info":[{"award-number":["24K15098"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Cluster Comput"],"published-print":{"date-parts":[[2025,10]]},"DOI":"10.1007\/s10586-025-05366-1","type":"journal-article","created":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T12:55:49Z","timestamp":1757595349000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Dynamic fitness-distance balance competitive swarm optimizer: performance investigation, engineering Simulation, and application in superconductor critical temperature prediction"],"prefix":"10.1007","volume":"28","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-8394-1474","authenticated-orcid":false,"given":"Yang","family":"Cao","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-3117-6083","authenticated-orcid":false,"given":"Xingbang","family":"Du","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5029-0294","authenticated-orcid":false,"given":"Jun","family":"Yu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4605-5579","authenticated-orcid":false,"given":"Rui","family":"Zhong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5750-9217","authenticated-orcid":false,"given":"Masaharu","family":"Munetomo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,9,11]]},"reference":[{"key":"5366_CR1","doi-asserted-by":"crossref","first-page":"112194","DOI":"10.1016\/j.knosys.2024.112194","volume":"300","author":"J Ji","year":"2024","unstructured":"Ji, J., Wu, T., Yang, C.: Neural population dynamics optimization algorithm: a novel brain-inspired meta-heuristic method. Knowl. Based Syst. 300, 112194 (2024)","journal-title":"Knowl. Based Syst."},{"key":"5366_CR2","doi-asserted-by":"crossref","first-page":"112561","DOI":"10.1016\/j.asoc.2024.112561","volume":"169","author":"X Zhong","year":"2024","unstructured":"Zhong, X., Liang, B.: Elite-based butterfly optimization algorithm and its application in speckle projection technique. Appl. Soft Comput. 169, 112561 (2024)","journal-title":"Appl. Soft Comput."},{"key":"5366_CR3","doi-asserted-by":"crossref","first-page":"111880","DOI":"10.1016\/j.knosys.2024.111880","volume":"296","author":"S Oladejo","year":"2024","unstructured":"Oladejo, S., Ekwe, S., Mirjalili, S.: The hiking optimization algorithm: a novel human-based metaheuristic approach. Knowl. Based Syst. 296, 111880 (2024)","journal-title":"Knowl. Based Syst."},{"key":"5366_CR4","first-page":"1","volume":"10","author":"L Xiao","year":"2024","unstructured":"Xiao, L., Zhang, Z., Huang, K., Jiang, J., Peng, Y.: Noise optimization in artificial neural networks. IEEE Trans. Autom. Sci. Eng. 10, 1\u201314 (2024)","journal-title":"IEEE Trans. Autom. Sci. Eng."},{"key":"5366_CR5","doi-asserted-by":"crossref","first-page":"101779","DOI":"10.1016\/j.swevo.2024.101779","volume":"91","author":"M Ghazaan","year":"2024","unstructured":"Ghazaan, M., Salmani Oshnari, A., Salmani Oshnari, A.: A novel adaptive optimization scheme for advancing metaheuristics and global optimization. Swarm Evol. Comput. 91, 101779 (2024)","journal-title":"Swarm Evol. Comput."},{"issue":"5","key":"5366_CR6","first-page":"88","volume":"17","author":"T Hamadneh","year":"2024","unstructured":"Hamadneh, T., Batiha, B., Alsayyed, O., Bektemyssova, G., Montazeri, Z., Dehghani, M., Eguchi, K.: On the application of potter optimization algorithm for solving supply chain management application. Int. J. Intell. Eng. Syst. 17(5), 88 (2024)","journal-title":"Int. J. Intell. Eng. Syst."},{"issue":"4","key":"5366_CR7","first-page":"230","volume":"17","author":"S Alomari","year":"2024","unstructured":"Alomari, S., Kaabneh, K., AbuFalahah, I., Gochhait, S., Leonova, I., Montazeri, Z., Dehghani, M., Eguchi, K.: Carpet weaver optimization: a novel simple and effective human-inspired metaheuristic algorithm. Int. J. Intell. Eng. Syst. 17(4), 230 (2024)","journal-title":"Int. J. Intell. Eng. Syst."},{"key":"5366_CR8","first-page":"1038","volume":"17","author":"T Hamadneh","year":"2024","unstructured":"Hamadneh, T., Batiha, B., Werner, F., Montazeri, Z., Dehghani, M., Gulnara, B., Eguchi, K.: Fossa optimization algorithm: a new bio-inspired metaheuristic algorithm for engineering applications. Int. J. Intell. Eng. Syst. 17, 1038\u20131047 (2024)","journal-title":"Int. J. Intell. Eng. Syst."},{"key":"5366_CR9","first-page":"732","volume":"17","author":"T Hamadneh","year":"2024","unstructured":"Hamadneh, T., Kaabneh, K., Alssayed, O., Eguchi, K., Gochhait, D.S., Leonova, I., Dehghani, M.: Addax optimization algorithm: a novel nature-inspired optimizer for solving engineering applications. Int. J. Intell. Eng. Syst. 17, 732\u2013743 (2024)","journal-title":"Int. J. Intell. Eng. Syst."},{"key":"5366_CR10","first-page":"816","volume":"17","author":"S Omari","year":"2024","unstructured":"Omari, S., Kaabneh, K., Abufalahah, I., Eguchi, K., Gochhait, D.S., Leonova, I., Montazeri, Z., Dehghani, M.: Dollmaker optimization algorithm: a novel human-inspired optimizer for solving optimization problems. Int. J. Intell. Eng. Syst. 17, 816\u2013828 (2024)","journal-title":"Int. J. Intell. Eng. Syst."},{"key":"5366_CR11","first-page":"25","volume":"13","author":"T Hamadneh","year":"2024","unstructured":"Hamadneh, T., Batiha, B., Al Baik, O., Gulnara, B., Montazeri, Z., Werner, F., Dhiman, G., Dehghani, M., Eguchi, K.: Sales training based optimization: a new human-inspired metaheuristic approach for supply chain management. Int. J. Intell. Eng. Syst. 13, 25 (2024)","journal-title":"Int. J. Intell. Eng. Syst."},{"key":"5366_CR12","first-page":"2025","volume":"18","author":"T Hamadneh","year":"2024","unstructured":"Hamadneh, T., Batiha, B., Gharib, G., Montazeri, Z., Werner, F., Dhiman, G., Dehghani, M., Jawad, R., Aram, E., Ibraheem, I., Eguchi, K.: Orangutan optimization algorithm: an innovative bio-inspired metaheuristic approach for solving engineering optimization problems. Int. J. Intell. Eng. Syst. 18, 2025 (2024)","journal-title":"Int. J. Intell. Eng. Syst."},{"key":"5366_CR13","first-page":"2025","volume":"18","author":"T Hamadneh","year":"2024","unstructured":"Hamadneh, T., Batiha, B., Al Baik, O., Montazeri, Z., Parkash, O., Werner, F., Dhiman, G., Dehghani, M., Eguchi, K.: Spider-tailed horned viper optimization: an effective bio-inspired metaheuristic algorithm for solving engineering applications. Int. J. Intell. Eng. Syst. 18, 2025 (2024)","journal-title":"Int. J. Intell. Eng. Syst."},{"key":"5366_CR14","doi-asserted-by":"crossref","first-page":"115426","DOI":"10.1016\/j.oceaneng.2023.115426","volume":"285","author":"Y Yuan","year":"2023","unstructured":"Yuan, Y., Shen, Q., Xi, W., Wang, S., Ren, J., Yu, J., Yang, Q.: Multidisciplinary design optimization of dynamic positioning system for semi-submersible platform. Ocean Eng. 285, 115426 (2023)","journal-title":"Ocean Eng."},{"key":"5366_CR15","first-page":"1","volume":"32","author":"Y Yuan","year":"2024","unstructured":"Yuan, Y., Yang, Q., Ren, J., Mu, X., Wang, Z., Shen, Q., Li, Y.: Short-term power load forecasting based on skdr hybrid model. Electr. Eng. 32, 1\u201317 (2024)","journal-title":"Electr. Eng."},{"key":"5366_CR16","doi-asserted-by":"crossref","first-page":"120211","DOI":"10.1016\/j.renene.2024.120211","volume":"225","author":"Y Yuan","year":"2024","unstructured":"Yuan, Y., Yang, Q., Ren, J., Mu, X., Wang, Z., Shen, Q., Zhao, W.: Attack-defense strategy assisted osprey optimization algorithm for pemfc parameters identification. Renewable Energy 225, 120211 (2024)","journal-title":"Renewable Energy"},{"key":"5366_CR17","doi-asserted-by":"crossref","first-page":"102132","DOI":"10.1016\/j.jksuci.2024.102132","volume":"36","author":"L Kong","year":"2024","unstructured":"Kong, L., Jasser, M.B., Ajibade, S., Wagdy, A.: A systematic review on software reliability prediction via swarm intelligence algorithms. J. King Saud Univ. Comput. Inf. Sci. 36, 102132 (2024)","journal-title":"J. King Saud Univ. Comput. Inf. Sci."},{"key":"5366_CR18","doi-asserted-by":"crossref","first-page":"111047","DOI":"10.1016\/j.asoc.2023.111047","volume":"150","author":"GH Valencia-Rivera","year":"2024","unstructured":"Valencia-Rivera, G.H., Benavides-Robles, M.T., Vela Morales, A., Amaya, I., Cruz-Duarte, J.M., Ortiz-Bayliss, J.C., Avina-Cervantes, J.G.: A systematic review of metaheuristic algorithms in electric power systems optimization. Appl. Soft Comput. 150, 111047 (2024)","journal-title":"Appl. Soft Comput."},{"key":"5366_CR19","doi-asserted-by":"crossref","first-page":"124857","DOI":"10.1016\/j.eswa.2024.124857","volume":"255","author":"G Li","year":"2024","unstructured":"Li, G., Zhang, T., Tsai, C.-Y., Yao, L., Lu, Y., Tang, J.: Review of the metaheuristic algorithms in applications: visual analysis based on bibliometrics. Exp. Syst. Appl. 255, 124857 (2024)","journal-title":"Exp. Syst. Appl."},{"issue":"2","key":"5366_CR20","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1109\/TCYB.2014.2322602","volume":"45","author":"R Cheng","year":"2015","unstructured":"Cheng, R., Jin, Y.: A competitive swarm optimizer for large scale optimization. IEEE Trans. Cybern. 45(2), 191\u2013204 (2015)","journal-title":"IEEE Trans. Cybern."},{"issue":"10","key":"5366_CR21","doi-asserted-by":"crossref","first-page":"1627","DOI":"10.1109\/JAS.2021.1004129","volume":"8","author":"J Tang","year":"2021","unstructured":"Tang, J., Liu, G., Pan, Q.: A review on representative swarm intelligence algorithms for solving optimization problems: applications and trends. IEEE\/CAA J. Autom. Sinica 8(10), 1627\u20131643 (2021)","journal-title":"IEEE\/CAA J. Autom. Sinica"},{"key":"5366_CR22","doi-asserted-by":"crossref","first-page":"100868","DOI":"10.1016\/j.swevo.2021.100868","volume":"63","author":"EH Houssein","year":"2021","unstructured":"Houssein, E.H., Gad, A.G., Hussain, K., Suganthan, P.N.: Major advances in particle swarm optimization: theory, analysis, and application. Swarm Evol. Comput. 63, 100868 (2021)","journal-title":"Swarm Evol. Comput."},{"issue":"3","key":"5366_CR23","doi-asserted-by":"crossref","first-page":"1663","DOI":"10.1007\/s11831-022-09849-x","volume":"30","author":"J Nayak","year":"2023","unstructured":"Nayak, J., Swapnarekha, H., Naik, B., Dhiman, G., Vimal, S.: 25 years of particle swarm optimization: flourishing voyage of two decades. Arch. Comput. Methods Eng. 30(3), 1663\u20131725 (2023)","journal-title":"Arch. Comput. Methods Eng."},{"key":"5366_CR24","doi-asserted-by":"crossref","unstructured":"Ertenlice, O., Kalayci, C.: A survey of swarm intelligence for portfolio optimization: Algorithms and applications, Swarm and Evolutionary Computation 39 (02 2018)","DOI":"10.1016\/j.swevo.2018.01.009"},{"key":"5366_CR25","doi-asserted-by":"crossref","first-page":"101649","DOI":"10.1016\/j.swevo.2024.101649","volume":"89","author":"H Jin","year":"2024","unstructured":"Jin, H., Wang, X., Cheng, S., Sun, Y., Zhang, M., Lu, H., Wu, H., Shi, Y.: Solving dynamic multimodal optimization problems via a niching-based brain storm optimization with two archives algorithm. Swarm Evol. Comput. 89, 101649 (2024)","journal-title":"Swarm Evol. Comput."},{"key":"5366_CR26","doi-asserted-by":"crossref","first-page":"108254","DOI":"10.1016\/j.asoc.2021.108254","volume":"116","author":"A Jaafari","year":"2021","unstructured":"Jaafari, A., Panahi, M., Mafi-Gholami, D., Rahmati, O., Shahabi, H., Shirzadi, A., Lee, S., Bui, D., Pradhan, B.: Swarm intelligence optimization of the group method of data handling using the cuckoo search and whale optimization algorithms to model and predict landslides. Appl. Soft Comput. 116, 108254 (2021)","journal-title":"Appl. Soft Comput."},{"key":"5366_CR27","doi-asserted-by":"crossref","first-page":"101253","DOI":"10.1016\/j.swevo.2023.101253","volume":"77","author":"W Li","year":"2023","unstructured":"Li, W., Zhang, T., Wang, R., Huang, S., Liang, J.: Multimodal multi-objective optimization: comparative study of the state-of-the-art. Swarm Evol. Comput. 77, 101253 (2023)","journal-title":"Swarm Evol. Comput."},{"key":"5366_CR28","doi-asserted-by":"crossref","unstructured":"Cao, Y., Zhong, R., Yu, J., Munetomo, M.: Optimization of electricity consumption forecasting models via hyper-heuristic algorithm, In: 2024 6th International Conference on Data-driven Optimization of Complex Systems (DOCS), pp. 114\u2013120 (2024)","DOI":"10.1109\/DOCS63458.2024.10704338"},{"key":"5366_CR29","doi-asserted-by":"crossref","first-page":"108973","DOI":"10.1016\/j.compchemeng.2024.108973","volume":"194","author":"C-M Wen","year":"2024","unstructured":"Wen, C.-M., Ierapetritou, M.: Topology-informed derivative-free metaheuristic optimization method. Comput. Chem. Eng. 194, 108973 (2024)","journal-title":"Comput. Chem. Eng."},{"key":"5366_CR30","doi-asserted-by":"crossref","first-page":"111522","DOI":"10.1016\/j.asoc.2024.111522","volume":"157","author":"J Li","year":"2024","unstructured":"Li, J., Li, X., Gao, L.: An operator-inspired framework for metaheuristics and its applications on job-shop scheduling problems. Appl. Soft Comput. 157, 111522 (2024)","journal-title":"Appl. Soft Comput."},{"issue":"2","key":"5366_CR31","doi-asserted-by":"crossref","first-page":"271","DOI":"10.1016\/j.ejor.2024.03.020","volume":"320","author":"U Sadana","year":"2025","unstructured":"Sadana, U., Chenreddy, A., Delage, E., Forel, A., Frejinger, E., Vidal, T.: A survey of contextual optimization methods for decision-making under uncertainty. Eur. J. Oper. Res. 320(2), 271\u2013289 (2025)","journal-title":"Eur. J. Oper. Res."},{"key":"5366_CR32","doi-asserted-by":"crossref","first-page":"109580","DOI":"10.1109\/ACCESS.2022.3208169","volume":"10","author":"B Raj","year":"2022","unstructured":"Raj, B., Ahmedy, I., Idris, M.Y.I., Noor, R.M.: A hybrid sperm swarm optimization and genetic algorithm for unimodal and multimodal optimization problems. IEEE Access 10, 109580\u2013109596 (2022)","journal-title":"IEEE Access"},{"key":"5366_CR33","doi-asserted-by":"crossref","first-page":"4789","DOI":"10.1109\/ACCESS.2025.3525603","volume":"13","author":"A Solak","year":"2025","unstructured":"Solak, A., Onat, A., Kilin\u00e7, O.: An improved bare bones particle swarm optimization algorithm based on sequential update mechanism and a modified structure. IEEE Access 13, 4789\u20134814 (2025)","journal-title":"IEEE Access"},{"issue":"2","key":"5366_CR34","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1108\/IJCS-07-2020-0013","volume":"5","author":"J Liu","year":"2021","unstructured":"Liu, J., Liang, B., Ji, W.: An anomaly detection approach based on hybrid differential evolution and k-means clustering in crowd intelligence. Int. J. Crowd Sci. 5(2), 129\u2013142 (2021)","journal-title":"Int. J. Crowd Sci."},{"key":"5366_CR35","first-page":"11","volume":"190","author":"HT Kahraman","year":"2019","unstructured":"Kahraman, H.T., Aras, S., Gedikli, E.: Fitness-distance balance (fdb): a new selection method for meta-heuristic search algorithms. Knowl. Based Syst. 190, 11 (2019)","journal-title":"Knowl. Based Syst."},{"key":"5366_CR36","doi-asserted-by":"crossref","first-page":"110883","DOI":"10.1016\/j.optlastec.2024.110883","volume":"176","author":"Q Liu","year":"2024","unstructured":"Liu, Q., Sun, K., Tang, X., Huo, J.: Camera calibration based on lightweight fan-shaped target detection and fitness-distance-balance chaotic marine predators algorithm. Opt. Laser Technol. 176, 110883 (2024)","journal-title":"Opt. Laser Technol."},{"key":"5366_CR37","doi-asserted-by":"crossref","first-page":"171548","DOI":"10.1016\/j.ijleo.2023.171548","volume":"296","author":"M El Marghichi","year":"2023","unstructured":"El Marghichi, M., Dangoury, S.: Electrical parameters identification for three diode photovoltaic based on the manta ray foraging optimization with dynamic fitness distance balance. Optik 296, 171548 (2023)","journal-title":"Optik"},{"key":"5366_CR38","doi-asserted-by":"crossref","first-page":"123499","DOI":"10.1016\/j.apenergy.2024.123499","volume":"368","author":"B \u00d6zkaya","year":"2024","unstructured":"\u00d6zkaya, B.: Enhanced growth optimizer algorithm with dynamic fitness-distance balance method for solution of security-constrained optimal power flow problem in the presence of stochastic wind and solar energy. Appl. Energy 368, 123499 (2024)","journal-title":"Appl. Energy"},{"key":"5366_CR39","doi-asserted-by":"crossref","first-page":"100821","DOI":"10.1016\/j.swevo.2020.100821","volume":"61","author":"S Aras","year":"2020","unstructured":"Aras, S., Gedikli, E., Kahraman, H.T.: A novel stochastic fractal search algorithm with fitness-distance balance for global numerical optimization. Swarm Evol. Comput. 61, 100821 (2020)","journal-title":"Swarm Evol. Comput."},{"key":"5366_CR40","doi-asserted-by":"crossref","first-page":"04","DOI":"10.1016\/j.asoc.2021.107421","volume":"108","author":"U Guvenc","year":"2021","unstructured":"Guvenc, U., Duman, S., Kahraman, H.T., Aras, S., Kati, M.: Fitness-distance balance based adaptive guided differential evolution algorithm for security-constrained optimal power flow problem incorporating renewable energy sources. Appl. Soft Comput. 108, 04 (2021)","journal-title":"Appl. Soft Comput."},{"key":"5366_CR41","doi-asserted-by":"crossref","first-page":"122460","DOI":"10.1016\/j.eswa.2023.122460","volume":"240","author":"H Bak\u0131r","year":"2024","unstructured":"Bak\u0131r, H.: Dynamic fitness-distance balance-based artificial rabbits optimization algorithm to solve optimal power flow problem. Exp. Syst. Appl. 240, 122460 (2024)","journal-title":"Exp. Syst. Appl."},{"key":"5366_CR42","doi-asserted-by":"crossref","first-page":"102149","DOI":"10.1016\/j.jocs.2023.102149","volume":"74","author":"D Zhu","year":"2023","unstructured":"Zhu, D., Wang, S., Shen, J., Zhou, C., Li, T., Yan, S.: A multi-strategy particle swarm algorithm with exponential noise and fitness-distance balance method for low-altitude penetration in secure space. J. Comput. Sci. 74, 102149 (2023)","journal-title":"J. Comput. Sci."},{"key":"5366_CR43","doi-asserted-by":"crossref","first-page":"122032","DOI":"10.1016\/j.apenergy.2023.122032","volume":"353","author":"Q Liu","year":"2024","unstructured":"Liu, Q., Zhang, C., Li, Z., Peng, T., Zhang, Z., Du, D., Nazir, M.S.: Multi-strategy adaptive guidance differential evolution algorithm using fitness-distance balance and opposition-based learning for constrained global optimization of photovoltaic cells and modules. Appl. Energy 353, 122032 (2024)","journal-title":"Appl. Energy"},{"key":"5366_CR44","first-page":"12","volume":"22","author":"N Van Thieu","year":"2024","unstructured":"Van Thieu, N.: Opfunu: an open-source python library for optimization benchmark functions. J. Open Res. Softw. 22, 12 (2024)","journal-title":"J. Open Res. Softw."},{"key":"5366_CR45","doi-asserted-by":"crossref","first-page":"102871","DOI":"10.1016\/j.sysarc.2023.102871","volume":"139","author":"N Van Thieu","year":"2023","unstructured":"Van Thieu, N., Mirjalili, S.: Mealpy: an open-source library for latest meta-heuristic algorithms in python. J. Syst. Arch. 139, 102871 (2023)","journal-title":"J. Syst. Arch."},{"key":"5366_CR46","doi-asserted-by":"crossref","first-page":"129034","DOI":"10.1016\/j.jhydrol.2022.129034","volume":"617","author":"N Van Thieu","year":"2023","unstructured":"Van Thieu, N., Barma, S.D., Van Lam, T., Kisi, O., Mahesha, A.: Groundwater level modeling using augmented artificial ecosystem optimization. J. Hydrol. 617, 129034 (2023)","journal-title":"J. Hydrol."},{"key":"5366_CR47","doi-asserted-by":"crossref","first-page":"107282","DOI":"10.1016\/j.asoc.2021.107282","volume":"105","author":"AN Ahmed","year":"2021","unstructured":"Ahmed, A.N., Van Lam, T., Hung, N.D., Van Thieu, N., Kisi, O., El-Shafie, A.: A comprehensive comparison of recent developed meta-heuristic algorithms for streamflow time series forecasting problem. Appl. Soft Comput. 105, 107282 (2021)","journal-title":"Appl. Soft Comput."}],"container-title":["Cluster Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-025-05366-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10586-025-05366-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-025-05366-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,8]],"date-time":"2025-10-08T17:31:44Z","timestamp":1759944704000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10586-025-05366-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,11]]},"references-count":47,"journal-issue":{"issue":"11","published-print":{"date-parts":[[2025,10]]}},"alternative-id":["5366"],"URL":"https:\/\/doi.org\/10.1007\/s10586-025-05366-1","relation":{},"ISSN":["1386-7857","1573-7543"],"issn-type":[{"value":"1386-7857","type":"print"},{"value":"1573-7543","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9,11]]},"assertion":[{"value":"24 January 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 March 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 April 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 September 2025","order":4,"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 no Conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"745"}}