{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,20]],"date-time":"2026-04-20T17:39:32Z","timestamp":1776706772376,"version":"3.51.2"},"reference-count":59,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"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":["Int J Syst Assur Eng Manag"],"published-print":{"date-parts":[[2025,1]]},"DOI":"10.1007\/s13198-024-02609-z","type":"journal-article","created":{"date-parts":[[2025,1,14]],"date-time":"2025-01-14T00:59:38Z","timestamp":1736816378000},"page":"254-309","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["A novel hybrid ESO-DE-WHO algorithm for solving real-engineering optimization problems"],"prefix":"10.1007","volume":"16","author":[{"given":"Damodar","family":"Panigrahy","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4811-8150","authenticated-orcid":false,"given":"Padarbinda","family":"Samal","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,1,14]]},"reference":[{"key":"2609_CR1","doi-asserted-by":"publisher","DOI":"10.5120\/ijca2016909119","author":"M Abdel-Baset","year":"2016","unstructured":"Abdel-Baset M, Hezam I (2016) A hybrid flower pollination algorithm for engineering optimization problems. Int J Comput Appl. https:\/\/doi.org\/10.5120\/ijca2016909119","journal-title":"Int J Comput Appl"},{"key":"2609_CR2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2990893","author":"M Abdel-Basset","year":"2020","unstructured":"Abdel-Basset M, Mohamed R, Elhoseny M et al (2020) A hybrid COVID-19 detection model using an improved marine predators algorithm and a ranking-based diversity reduction strategy. IEEE Access. https:\/\/doi.org\/10.1109\/ACCESS.2020.2990893","journal-title":"IEEE Access"},{"key":"2609_CR3","doi-asserted-by":"publisher","DOI":"10.1016\/j.cma.2020.113609","volume":"376","author":"L Abualigah","year":"2021","unstructured":"Abualigah L, Diabat A, Mirjalili S et al (2021) The arithmetic optimization algorithm. Comput Methods Appl Mech Eng 376:113690. https:\/\/doi.org\/10.1016\/j.cma.2020.113609","journal-title":"Comput Methods Appl Mech Eng"},{"key":"2609_CR4","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2020.06.037","author":"I Ahmadianfar","year":"2020","unstructured":"Ahmadianfar I, Bozorg-Haddad O, Chu X (2020) Gradient-based optimizer: a new metaheuristic optimization algorithm. Inf Sci (Ny). https:\/\/doi.org\/10.1016\/j.ins.2020.06.037","journal-title":"Inf Sci (Ny)"},{"key":"2609_CR5","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2020.113308","author":"YA Anita","year":"2020","unstructured":"Anita YA, Kumar N (2020) Artificial electric field algorithm for engineering optimization problems. Expert Syst Appl. https:\/\/doi.org\/10.1016\/j.eswa.2020.113308","journal-title":"Expert Syst Appl"},{"key":"2609_CR6","doi-asserted-by":"publisher","DOI":"10.1007\/s00500-018-3102-4","author":"S Arora","year":"2019","unstructured":"Arora S, Singh S (2019) Butterfly optimization algorithm: a novel approach for global optimization. Soft Comput. https:\/\/doi.org\/10.1007\/s00500-018-3102-4","journal-title":"Soft Comput"},{"key":"2609_CR7","doi-asserted-by":"publisher","DOI":"10.1007\/s00366-021-01364-0","author":"A Ates","year":"2021","unstructured":"Ates A, Akpamukcu M (2021) Optimization to optimization (OtoO): optimize monarchy butterfly method with stochastics multi-parameter divergence method for benchmark functions and load frequency control. Eng Comput. https:\/\/doi.org\/10.1007\/s00366-021-01364-0","journal-title":"Eng Comput"},{"key":"2609_CR8","doi-asserted-by":"publisher","DOI":"10.1007\/s12351-018-0427-9","author":"A Baykaso\u011flu","year":"2020","unstructured":"Baykaso\u011flu A, Ozsoydan FB, Senol ME (2020) Weighted superposition attraction algorithm for binary optimization problems. Oper Res. https:\/\/doi.org\/10.1007\/s12351-018-0427-9","journal-title":"Oper Res"},{"key":"2609_CR9","doi-asserted-by":"publisher","DOI":"10.1155\/2021\/6639671","author":"Y Che","year":"2021","unstructured":"Che Y, He D (2021) A hybrid whale optimization with seagull algorithm for global optimization problems. Math Probl Eng. https:\/\/doi.org\/10.1155\/2021\/6639671","journal-title":"Math Probl Eng"},{"key":"2609_CR10","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2018.11.024","author":"G Dhiman","year":"2019","unstructured":"Dhiman G, Kumar V (2019) Seagull optimization algorithm: theory and its applications for large-scale industrial engineering problems. Knowledge-Based Syst. https:\/\/doi.org\/10.1016\/j.knosys.2018.11.024","journal-title":"Knowledge-Based Syst"},{"key":"2609_CR11","doi-asserted-by":"publisher","DOI":"10.1016\/j.yofte.2021.102559","volume":"64","author":"L Duan","year":"2021","unstructured":"Duan L, Zhou H, Tan S et al (2021) Improved particle swarm optimization algorithm for enhanced coupling of coaxial optical communication laser. Opt Fiber Technol 64:102559. https:\/\/doi.org\/10.1016\/j.yofte.2021.102559","journal-title":"Opt Fiber Technol"},{"key":"2609_CR12","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3007928","author":"MA Elaziz","year":"2020","unstructured":"Elaziz MA, Ewees AA, Yousri D et al (2020) An improved marine predators algorithm with fuzzy entropy for multi-level thresholding: real world example of COVID-19 CT image segmentation. IEEE Access. https:\/\/doi.org\/10.1109\/ACCESS.2020.3007928","journal-title":"IEEE Access"},{"key":"2609_CR13","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2020.113377","volume":"152","author":"A Faramarzi","year":"2020","unstructured":"Faramarzi A, Heidarinejad M, Mirjalili S, Gandomi AH (2020) Marine predators algorithm: a nature-inspired metaheuristic. Expert Syst Appl 152:113377. https:\/\/doi.org\/10.1016\/j.eswa.2020.113377","journal-title":"Expert Syst Appl"},{"key":"2609_CR14","doi-asserted-by":"publisher","DOI":"10.1007\/s00366-011-0241-y","author":"AH Gandomi","year":"2013","unstructured":"Gandomi AH, Yang XS, Alavi AH (2013) Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems. Eng Comput. https:\/\/doi.org\/10.1007\/s00366-011-0241-y","journal-title":"Eng Comput"},{"key":"2609_CR15","doi-asserted-by":"publisher","DOI":"10.1007\/s00500-017-2804-3","author":"MR Ghasemi","year":"2019","unstructured":"Ghasemi MR, Varaee H (2019) Damping vibration-based IGMM optimization algorithm: fast and significant. Soft Comput. https:\/\/doi.org\/10.1007\/s00500-017-2804-3","journal-title":"Soft Comput"},{"key":"2609_CR16","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-020-09906-6","author":"AH Halim","year":"2021","unstructured":"Halim AH, Ismail I, Das S (2021) Performance assessment of the metaheuristic optimization algorithms: an exhaustive review. Artif Intell Rev. https:\/\/doi.org\/10.1007\/s10462-020-09906-6","journal-title":"Artif Intell Rev"},{"key":"2609_CR17","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-020-01893-z","author":"FA Hashim","year":"2021","unstructured":"Hashim FA, Hussain K, Houssein EH et al (2021) Archimedes optimization algorithm: a new metaheuristic algorithm for solving optimization problems. Appl Intell. https:\/\/doi.org\/10.1007\/s10489-020-01893-z","journal-title":"Appl Intell"},{"key":"2609_CR18","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2019.103249","author":"V Hayyolalam","year":"2020","unstructured":"Hayyolalam V, Pourhaji Kazem AA (2020) Black widow optimization algorithm: a novel meta-heuristic approach for solving engineering optimization problems. Eng Appl Artif Intell. https:\/\/doi.org\/10.1016\/j.engappai.2019.103249","journal-title":"Eng Appl Artif Intell"},{"key":"2609_CR19","doi-asserted-by":"publisher","first-page":"849","DOI":"10.1016\/j.future.2019.02.028","volume":"97","author":"AA Heidari","year":"2019","unstructured":"Heidari AA, Mirjalili S, Faris H et al (2019) Harris hawks optimization: algorithm and applications. Futur Gener Comput Syst 97:849\u2013872. https:\/\/doi.org\/10.1016\/j.future.2019.02.028","journal-title":"Futur Gener Comput Syst"},{"key":"2609_CR20","doi-asserted-by":"publisher","DOI":"10.1080\/03052150701252664","author":"YL Hsu","year":"2007","unstructured":"Hsu YL, Liu TC (2007) Developing a fuzzy proportional-derivative controller optimization engine for engineering design optimization problems. Eng Optim. https:\/\/doi.org\/10.1080\/03052150701252664","journal-title":"Eng Optim"},{"key":"2609_CR21","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2021.104417","volume":"105","author":"G Hu","year":"2021","unstructured":"Hu G, Zhu X, Wei G, Ter CC (2021) An improved marine predators algorithm for shape optimization of developable ball surfaces. Eng Appl Artif Intell 105:104417. https:\/\/doi.org\/10.1016\/j.engappai.2021.104417","journal-title":"Eng Appl Artif Intell"},{"key":"2609_CR22","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2020.103541","volume":"90","author":"S Kaur","year":"2020","unstructured":"Kaur S, Awasthi LK, Sangal AL, Dhiman G (2020) Tunicate swarm algorithm: a new bio-inspired based metaheuristic paradigm for global optimization. Eng Appl Artif Intell 90:103541. https:\/\/doi.org\/10.1016\/j.engappai.2020.103541","journal-title":"Eng Appl Artif Intell"},{"key":"2609_CR23","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1016\/j.compstruc.2016.01.008","volume":"167","author":"A Kaveh","year":"2016","unstructured":"Kaveh A, Bakhshpoori T (2016) Water evaporation optimization: a novel physically inspired optimization algorithm. Comput Struct 167:69\u201385. https:\/\/doi.org\/10.1016\/j.compstruc.2016.01.008","journal-title":"Comput Struct"},{"key":"2609_CR24","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1016\/j.advengsoft.2017.03.014","volume":"110","author":"A Kaveh","year":"2017","unstructured":"Kaveh A, Dadras A (2017) A novel meta-heuristic optimization algorithm: thermal exchange optimization. Adv Eng Softw 110:69\u201384. https:\/\/doi.org\/10.1016\/j.advengsoft.2017.03.014","journal-title":"Adv Eng Softw"},{"key":"2609_CR59","doi-asserted-by":"publisher","first-page":"108064","DOI":"10.1016\/j.compbiomed.2024.108064","volume":"172","author":"J Lian","year":"2024","unstructured":"Lian J et al (2024) Parrot optimizer: Algorithm and applications to medical problems. Comput Biol Med  172:108064","journal-title":"Comput Biol Med"},{"key":"2609_CR25","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2020.03.055","author":"S Li","year":"2020","unstructured":"Li S, Chen H, Wang M et al (2020) Slime mould algorithm: a new method for stochastic optimization. Futur Gener Comput Syst. https:\/\/doi.org\/10.1016\/j.future.2020.03.055","journal-title":"Futur Gener Comput Syst"},{"key":"2609_CR26","doi-asserted-by":"publisher","DOI":"10.1016\/j.advengsoft.2021.103009","volume":"157\u2013158","author":"SH Li","year":"2021","unstructured":"Li SH, Luo XH, Wu LZ (2021a) An improved whale optimization algorithm for locating critical slip surface of slopes. Adv Eng Softw 157\u2013158:103009. https:\/\/doi.org\/10.1016\/j.advengsoft.2021.103009","journal-title":"Adv Eng Softw"},{"key":"2609_CR27","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2021.107504","volume":"108","author":"LL Li","year":"2021","unstructured":"Li LL, Liu ZF, Tseng ML et al (2021b) Improved tunicate swarm algorithm: Solving the dynamic economic emission dispatch problems. Appl Soft Comput 108:107504. https:\/\/doi.org\/10.1016\/j.asoc.2021.107504","journal-title":"Appl Soft Comput"},{"key":"2609_CR28","doi-asserted-by":"publisher","DOI":"10.1016\/j.advengsoft.2016.01.008","author":"S Mirjalili","year":"2016","unstructured":"Mirjalili S, Lewis A (2016) The whale optimization algorithm. Adv Eng Softw. https:\/\/doi.org\/10.1016\/j.advengsoft.2016.01.008","journal-title":"Adv Eng Softw"},{"key":"2609_CR29","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1016\/j.advengsoft.2013.12.007","volume":"69","author":"S Mirjalili","year":"2014","unstructured":"Mirjalili S, Mirjalili SM, Lewis A (2014) Grey wolf optimizer. Adv Eng Softw 69:46\u201361. https:\/\/doi.org\/10.1016\/j.advengsoft.2013.12.007","journal-title":"Adv Eng Softw"},{"key":"2609_CR30","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-015-1870-7","author":"S Mirjalili","year":"2016","unstructured":"Mirjalili S, Mirjalili SM, Hatamlou A (2016) Multi-verse Optimizer: a nature-inspired algorithm for global optimization. Neural Comput Appl. https:\/\/doi.org\/10.1007\/s00521-015-1870-7","journal-title":"Neural Comput Appl"},{"key":"2609_CR31","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1016\/j.advengsoft.2017.07.002","volume":"114","author":"S Mirjalili","year":"2017","unstructured":"Mirjalili S, Gandomi AH, Mirjalili SZ et al (2017) Salp swarm algorithm: a bio-inspired optimizer for engineering design problems. Adv Eng Softw 114:163\u2013191. https:\/\/doi.org\/10.1016\/j.advengsoft.2017.07.002","journal-title":"Adv Eng Softw"},{"key":"2609_CR32","doi-asserted-by":"publisher","DOI":"10.5267\/j.dsl.2017.6.006","author":"S Nama","year":"2018","unstructured":"Nama S, Saha AK (2018) An ensemble symbiosis organisms search algorithm and its application to real world problems. Decis Sci Lett. https:\/\/doi.org\/10.5267\/j.dsl.2017.6.006","journal-title":"Decis Sci Lett"},{"key":"2609_CR33","doi-asserted-by":"publisher","DOI":"10.1007\/s00366-021-01438-z","author":"I Naruei","year":"2021","unstructured":"Naruei I, Keynia F (2021a) Wild horse optimizer: a new meta-heuristic algorithm for solving engineering optimization problems. Eng Comput. https:\/\/doi.org\/10.1007\/s00366-021-01438-z","journal-title":"Eng Comput"},{"key":"2609_CR34","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.115352","volume":"183","author":"I Naruei","year":"2021","unstructured":"Naruei I, Keynia F (2021b) A new optimization method based on COOT bird natural life model. Expert Syst Appl 183:115352. https:\/\/doi.org\/10.1016\/j.eswa.2021.115352","journal-title":"Expert Syst Appl"},{"key":"2609_CR57","doi-asserted-by":"publisher","first-page":"14","DOI":"10.3390\/math11143210","volume":"11","author":"HM Nayyef","year":"2023","unstructured":"Nayyef HM, Ibrahim AA, Mohd Zainuri MAA, Zulkifley MA,   Shareef H (2023) A novel hybrid algorithm based on jellyfish search and particle swarm optimization. Mathematics  11(14):3210","journal-title":"Mathematics"},{"key":"2609_CR35","doi-asserted-by":"publisher","first-page":"783","DOI":"10.1007\/s13246-016-0468-4","volume":"39","author":"D Panigrahy","year":"2016","unstructured":"Panigrahy D, Sahu PK (2016) Extended Kalman smoother with differential evolution technique for denoising of ECG signal. Australas Phys Eng Sci Med 39:783\u2013795. https:\/\/doi.org\/10.1007\/s13246-016-0468-4","journal-title":"Australas Phys Eng Sci Med"},{"key":"2609_CR36","doi-asserted-by":"publisher","first-page":"197","DOI":"10.1007\/s13246-017-0527-5","volume":"40","author":"D Panigrahy","year":"2017","unstructured":"Panigrahy D, Sahu PK (2017) Extraction of fetal ECG signal by an improved method using extended Kalman smoother framework from single channel abdominal ECG signal. Australas Phys Eng Sci Med 40:197\u2013207. https:\/\/doi.org\/10.1007\/s13246-017-0527-5","journal-title":"Australas Phys Eng Sci Med"},{"key":"2609_CR37","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2021.104419","volume":"105","author":"D Panigrahy","year":"2021","unstructured":"Panigrahy D, Samal P (2021) Modified lightning search algorithm for optimization. Eng Appl Artif Intell 105:104419. https:\/\/doi.org\/10.1016\/j.engappai.2021.104419","journal-title":"Eng Appl Artif Intell"},{"key":"2609_CR38","doi-asserted-by":"publisher","DOI":"10.1016\/j.compeleceng.2021.107035","author":"D Panigrahy","year":"2021","unstructured":"Panigrahy D, Sahu PK, Albu F (2021) Detection of ventricular fibrillation rhythm by using boosted support vector machine with an optimal variable combination. Comput Electr Eng. https:\/\/doi.org\/10.1016\/j.compeleceng.2021.107035","journal-title":"Comput Electr Eng"},{"key":"2609_CR39","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1007\/s11721-007-0002-0","volume":"1","author":"R Poli","year":"2007","unstructured":"Poli R, Kennedy J, Blackwell T (2007) Particle swarm optimization. Swarm Intell 1:33\u201357","journal-title":"Swarm Intell"},{"key":"2609_CR40","doi-asserted-by":"publisher","first-page":"398","DOI":"10.1109\/TEVC.2008.927706","volume":"13","author":"AK Qin","year":"2009","unstructured":"Qin AK, Huang VL, Suganthan PN (2009) Differential evolution algorithm with strategy adaptation for global numerical optimization. IEEE Trans Evol Comput 13:398\u2013417. https:\/\/doi.org\/10.1109\/TEVC.2008.927706","journal-title":"IEEE Trans Evol Comput"},{"key":"2609_CR41","doi-asserted-by":"publisher","DOI":"10.1016\/j.apm.2020.03.024","author":"C Qu","year":"2020","unstructured":"Qu C, He W, Peng X, Peng X (2020) Harris hawks optimization with information exchange. Appl Math Model. https:\/\/doi.org\/10.1016\/j.apm.2020.03.024","journal-title":"Appl Math Model"},{"key":"2609_CR42","doi-asserted-by":"publisher","DOI":"10.1002\/9781119454816","volume-title":"Engineering optimization: theory and practice","author":"SS Rao","year":"2019","unstructured":"Rao SS (2019) Engineering optimization: theory and practice. Wiley"},{"key":"2609_CR43","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1016\/j.cad.2010.12.015","volume":"43","author":"RV Rao","year":"2011","unstructured":"Rao RV, Savsani VJ, Vakharia DP (2011) Teaching-learning-based optimization: A novel method for constrained mechanical design optimization problems. CAD Comput Aided Des 43:303\u2013315. https:\/\/doi.org\/10.1016\/j.cad.2010.12.015","journal-title":"CAD Comput Aided Des"},{"key":"2609_CR44","volume-title":"Engineering optimization methods and applications second edition","author":"A Ravindran","year":"2007","unstructured":"Ravindran A, Ragsdell KM, Reklaitis GV (2007) Engineering optimization methods and applications second edition. Wiley"},{"key":"2609_CR45","doi-asserted-by":"publisher","DOI":"10.1002\/jnm.2351","author":"P Samal","year":"2018","unstructured":"Samal P, Mohanty S, Ganguly S (2018) Modeling, optimal sizing, and allocation of DSTATCOM in unbalanced radial distribution systems using differential evolution algorithm. Int J Numer Model Electron Netw, Dev Fields. https:\/\/doi.org\/10.1002\/jnm.2351","journal-title":"Int J Numer Model Electron Netw, Dev Fields"},{"key":"2609_CR46","doi-asserted-by":"publisher","DOI":"10.1007\/s00500-019-03772-3","author":"P Samal","year":"2019","unstructured":"Samal P, Ganguly S, Mohanty S (2019) A fuzzy pragmatic DE\u2013CSA hybrid approach for unbalanced radial distribution system planning with distributed generation. Soft Comput. https:\/\/doi.org\/10.1007\/s00500-019-03772-3","journal-title":"Soft Comput"},{"key":"2609_CR47","doi-asserted-by":"publisher","first-page":"165","DOI":"10.1016\/j.engappai.2019.08.025","volume":"86","author":"SH Samareh Moosavi","year":"2019","unstructured":"Samareh Moosavi SH, Bardsiri VK (2019) Poor and rich optimization algorithm: a new human-based and multi populations algorithm. Eng Appl Artif Intell 86:165\u2013181. https:\/\/doi.org\/10.1016\/j.engappai.2019.08.025","journal-title":"Eng Appl Artif Intell"},{"key":"2609_CR48","doi-asserted-by":"publisher","DOI":"10.1016\/j.apm.2015.10.040","author":"P Savsani","year":"2016","unstructured":"Savsani P, Savsani V (2016) Passing vehicle search (PVS): a novel metaheuristic algorithm. Appl Math Model. https:\/\/doi.org\/10.1016\/j.apm.2015.10.040","journal-title":"Appl Math Model"},{"key":"2609_CR49","unstructured":"Suganthan PN, Hansen N, Liang JJ, et al (2020) Problem definitions and evaluation criteria for the CEC 2021 special session and competition on single objective bound constrained numerical optimization. Tech Report, Nanyang Technol Univ Singapore, May 2005 KanGAL Rep 2005005, IIT Kanpur, India"},{"key":"2609_CR56","doi-asserted-by":"publisher","first-page":"118679","DOI":"10.1016\/j.engstruct.2024.118679","volume":"318","author":"TN Truong","year":"2024","unstructured":"Truong TN,   Chou JS, (2024) Metaheuristic algorithm inspired by enterprise development for global optimization and structural engineering problems with frequency constraints. Eng Struct  318:118679","journal-title":"Eng Struct"},{"key":"2609_CR50","doi-asserted-by":"publisher","DOI":"10.1016\/j.aei.2021.101315","volume":"49","author":"Z Wang","year":"2021","unstructured":"Wang Z, Xuan J (2021) Intelligent fault recognition framework by using deep reinforcement learning with one dimension convolution and improved actor-critic algorithm. Adv Eng Informatics 49:101315. https:\/\/doi.org\/10.1016\/j.aei.2021.101315","journal-title":"Adv Eng Informatics"},{"issue":"1109\/4235","key":"2609_CR51","volume":"10","author":"DH Wolpert","year":"1997","unstructured":"Wolpert DH, Macready WG (1997) No free lunch theorems for optimization. IEEE Trans Evol Comput Doi 10(1109\/4235):585893","journal-title":"IEEE Trans Evol Comput Doi"},{"key":"2609_CR52","doi-asserted-by":"publisher","first-page":"447","DOI":"10.1016\/j.renene.2021.05.058","volume":"176","author":"Q Xie","year":"2021","unstructured":"Xie Q, Guo Z, Liu D et al (2021) Optimization of heliostat field distribution based on improved gray wolf optimization algorithm. Renew Energy 176:447\u2013458. https:\/\/doi.org\/10.1016\/j.renene.2021.05.058","journal-title":"Renew Energy"},{"key":"2609_CR53","doi-asserted-by":"publisher","DOI":"10.1016\/j.optlaseng.2021.106646","volume":"144","author":"Z Yang","year":"2021","unstructured":"Yang Z, Fang L, Zhang X, Zuo H (2021) Controlling a scattered field output of light passing through turbid medium using an improved ant colony optimization algorithm. Opt Lasers Eng 144:106646. https:\/\/doi.org\/10.1016\/j.optlaseng.2021.106646","journal-title":"Opt Lasers Eng"},{"key":"2609_CR58","doi-asserted-by":"publisher","first-page":"128427","DOI":"10.1016\/j.neucom.2024.128427","volume":"128427","author":"C Yuan","year":"2024","unstructured":"Yuan C, Zhao D,  Heidari AA,  Liu L,  Chen Y,  Chen H, (2024) Polar lights optimizer: Algorithm and applications in\nimage segmentation and feature selection. Neurocomputing  607:128427","journal-title":"Neurocomputing"},{"key":"2609_CR54","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.cor.2014.10.008","volume":"55","author":"YJ Zheng","year":"2015","unstructured":"Zheng YJ (2015) Water wave optimization: a new nature-inspired metaheuristic. Comput Oper Res 55:1\u201311. https:\/\/doi.org\/10.1016\/j.cor.2014.10.008","journal-title":"Comput Oper Res"},{"key":"2609_CR55","doi-asserted-by":"publisher","DOI":"10.1016\/j.istruc.2021.05.043","author":"H Zhou","year":"2021","unstructured":"Zhou H, Zhang G, Wang X et al (2021) Structural identification using improved butterfly optimization algorithm with adaptive sampling test and search space reduction method. Structures. https:\/\/doi.org\/10.1016\/j.istruc.2021.05.043","journal-title":"Structures"}],"container-title":["International Journal of System Assurance Engineering and Management"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13198-024-02609-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13198-024-02609-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13198-024-02609-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,24]],"date-time":"2025-02-24T08:54:45Z","timestamp":1740387285000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13198-024-02609-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1]]},"references-count":59,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2025,1]]}},"alternative-id":["2609"],"URL":"https:\/\/doi.org\/10.1007\/s13198-024-02609-z","relation":{},"ISSN":["0975-6809","0976-4348"],"issn-type":[{"value":"0975-6809","type":"print"},{"value":"0976-4348","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,1]]},"assertion":[{"value":"8 November 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 October 2024","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 November 2024","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 January 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 that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"This article does not contain any studies with human participants or animals performed by any of the authors.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}}]}}