{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T16:09:53Z","timestamp":1776874193913,"version":"3.51.2"},"reference-count":71,"publisher":"Springer Science and Business Media LLC","issue":"28","license":[{"start":{"date-parts":[[2024,6,14]],"date-time":"2024-06-14T00:00:00Z","timestamp":1718323200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,6,14]],"date-time":"2024-06-14T00:00:00Z","timestamp":1718323200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"Tokat Gaziosmanpasa University"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2024,10]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>When real-world engineering challenges are examined adequately, it becomes clear that multi-objective need to be optimized. Many engineering problems have been handled utilizing the decomposition-based optimization approach according to the literature. The performance of multi-objective evolutionary algorithms is highly dependent on the balance of convergence and diversity. Diversity and convergence are not appropriately balanced in the decomposition technique, as they are in many approaches, for real-world problems. A novel Multi-Objective Artificial Algae Algorithm based on Decomposition (MOAAA\/D) is proposed in the paper to solve multi-objective structural problems. MOAAA\/D is the first multi-objective algorithm that uses the decomposition-based method with the artificial algae algorithm. MOAAA\/D, which successfully draws a graph on 24 benchmark functions within the area of two common metrics, also produced promising results in the structural design problem to which it was applied. To facilitate the design of the \"rectangular reinforced concrete column\" using MOAAA\/D, a solution space was derived by optimizing the rebar ratio and the concrete quantity to be employed.<\/jats:p>","DOI":"10.1007\/s00521-024-09746-3","type":"journal-article","created":{"date-parts":[[2024,6,14]],"date-time":"2024-06-14T13:02:05Z","timestamp":1718370125000},"page":"17345-17374","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["MOAAA\/D: a decomposition-based novel algorithm and a structural design application"],"prefix":"10.1007","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4753-2867","authenticated-orcid":false,"given":"Mustafa","family":"Altiok","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mesut","family":"G\u00fcnd\u00fcz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,6,14]]},"reference":[{"key":"9746_CR1","doi-asserted-by":"crossref","first-page":"377","DOI":"10.1016\/j.asoc.2018.04.009","volume":"68","author":"A Babalik","year":"2018","unstructured":"Babalik A, Ozkis A, Uymaz SA, Kiran MS (2018) A multi-objective artificial algae algorithm. Appl Soft Comput 68:377\u2013395","journal-title":"Appl Soft Comput"},{"key":"9746_CR2","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1016\/j.ins.2017.03.026","volume":"402","author":"A \u00d6zk\u0131\u015f","year":"2017","unstructured":"\u00d6zk\u0131\u015f A, Babal\u0131k A (2017) A novel metaheuristic for multi-objective optimization problems: The multi-objective vortex search algorithm. Inf Sci 402:124\u2013148","journal-title":"Inf Sci"},{"issue":"1","key":"9746_CR3","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1109\/TFUZZ.2015.2426314","volume":"24","author":"Y Chi","year":"2015","unstructured":"Chi Y, Liu J (2015) Learning of fuzzy cognitive maps with varying densities using a multiobjective evolutionary algorithm. IEEE Trans Fuzzy Syst 24(1):71\u201381","journal-title":"IEEE Trans Fuzzy Syst"},{"key":"9746_CR4","doi-asserted-by":"crossref","first-page":"621","DOI":"10.1016\/j.asoc.2018.10.027","volume":"74","author":"Z Fan","year":"2019","unstructured":"Fan Z, Fang Y, Li W, Cai X, Wei C, Goodman E (2019) MOEA\/D with angle-based constrained dominance principle for constrained multi-objective optimization problems. Appl Soft Comput 74:621\u2013633","journal-title":"Appl Soft Comput"},{"key":"9746_CR5","doi-asserted-by":"crossref","first-page":"107582","DOI":"10.1016\/j.asoc.2021.107582","volume":"109","author":"\u00d6 \u0130nik","year":"2021","unstructured":"\u0130nik \u00d6, Alt\u0131ok M, \u00dclker E, Ko\u00e7er B (2021) MODE-CNN: A fast converging multi-objective optimization algorithm for CNN-based models. Appl Soft Comput 109:107582","journal-title":"Appl Soft Comput"},{"issue":"11","key":"9746_CR6","doi-asserted-by":"crossref","first-page":"8197","DOI":"10.1007\/s00521-022-08095-3","volume":"35","author":"M Altiok","year":"2023","unstructured":"Altiok M, Alakara EH, G\u00fcnd\u00fcz M, A\u011fao\u011flu MN (2023) A multi-objective genetic algorithm for the hot mix asphalt problem. Neural Comput Appl 35(11):8197\u20138225","journal-title":"Neural Comput Appl"},{"issue":"July","key":"9746_CR7","first-page":"416","volume":"93","author":"CM Fonseca","year":"1993","unstructured":"Fonseca CM, Fleming PJ (1993) Genetic algorithms for multiobjective optimization: formulationdiscussion and generalization. Icga 93(July):416\u2013423","journal-title":"Icga"},{"key":"9746_CR8","doi-asserted-by":"crossref","unstructured":"Horn J, Nafpliotis N, Goldberg DE (1994) A niched Pareto genetic algorithm for multiobjective optimization, In: Proceedings of the first IEEE conference on evolutionary computation. IEEE world congress on computational intelligence, IEEE, pp. 82\u201387.","DOI":"10.1109\/ICEC.1994.350037"},{"issue":"3","key":"9746_CR9","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1162\/evco.1994.2.3.221","volume":"2","author":"N Srinivas","year":"1994","unstructured":"Srinivas N, Deb K (1994) Muiltiobjective optimization using nondominated sorting in genetic algorithms. Evol Comput 2(3):221\u2013248","journal-title":"Evol Comput"},{"key":"9746_CR10","doi-asserted-by":"crossref","unstructured":"Coello CC, Lechuga MS, MOPSO: A proposal for multiple objective particle swarm optimization, In: Proceedings of the 2002 congress on evolutionary computation. CEC'02 (Cat. No. 02TH8600), vol. 2, pp. 1051\u20131056: IEEE.","DOI":"10.1109\/CEC.2002.1004388"},{"key":"9746_CR11","doi-asserted-by":"crossref","first-page":"115654","DOI":"10.1016\/j.eswa.2021.115654","volume":"185","author":"J Cao","year":"2021","unstructured":"Cao J, Zhang J, Zhao F, Chen Z (2021) A two-stage evolutionary strategy based MOEA\/D to multi-objective problems. Expert Syst Appl 185:115654","journal-title":"Expert Syst Appl"},{"issue":"2","key":"9746_CR12","doi-asserted-by":"crossref","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","journal-title":"IEEE Trans Evol Comput"},{"key":"9746_CR13","doi-asserted-by":"crossref","unstructured":"Chaudhari P, Thakur AK, Kumar R, Banerjee N, Kumar A (2022) Comparison of NSGA-III with NSGA-II for multi objective optimization of adiabatic styrene reactor, Materials Today: Proceedings 57:1509\u20131514","DOI":"10.1016\/j.matpr.2021.12.047"},{"key":"9746_CR14","doi-asserted-by":"crossref","first-page":"100025","DOI":"10.1016\/j.clscn.2021.100025","volume":"3","author":"X Wang","year":"2022","unstructured":"Wang X, Chen G, Xu S (2022) Bi-objective green supply chain network design under disruption risk through an extended NSGA-II algorithm. Cleaner Logistics and Supply Chain 3:100025","journal-title":"Cleaner Logistics and Supply Chain"},{"key":"9746_CR15","doi-asserted-by":"crossref","first-page":"106560","DOI":"10.1016\/j.asoc.2020.106560","volume":"96","author":"M Karakoyun","year":"2020","unstructured":"Karakoyun M, Ozkis A, Kodaz H (2020) A new algorithm based on gray wolf optimizer and shuffled frog leaping algorithm to solve the multi-objective optimization problems. Appl Soft Comput 96:106560","journal-title":"Appl Soft Comput"},{"key":"9746_CR16","doi-asserted-by":"crossref","unstructured":"Phan DH, Suzuki J (2013) R2-IBEA: R2 indicator based evolutionary algorithm for multiobjective optimization, In: 2013 IEEE congress on evolutionary computation, pp. 1836\u20131845: IEEE.","DOI":"10.1109\/CEC.2013.6557783"},{"key":"9746_CR17","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1016\/j.eswa.2016.11.007","volume":"71","author":"B Chabane","year":"2017","unstructured":"Chabane B, Basseur M, Hao J-K (2017) R2-IBMOLS applied to a practical case of the multiobjective knapsack problem. Expert Syst Appl 71:457\u2013468","journal-title":"Expert Syst Appl"},{"issue":"6","key":"9746_CR18","doi-asserted-by":"crossref","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","journal-title":"IEEE Trans Evol Comput"},{"key":"9746_CR19","doi-asserted-by":"crossref","first-page":"108481","DOI":"10.1016\/j.asoc.2022.108481","volume":"118","author":"W Wang","year":"2022","unstructured":"Wang W, Dai S, Zhao W, Wang C (2022) Multi-objective optimization of hexahedral pyramid crash box using MOEA\/D-DAE algorithm. Appl Soft Comput 118:108481","journal-title":"Appl Soft Comput"},{"key":"9746_CR20","doi-asserted-by":"crossref","first-page":"108832","DOI":"10.1016\/j.cep.2022.108832","volume":"173","author":"M Yang","year":"2022","unstructured":"Yang M, Gan Y, Gao L, Zhu X (2022) A structural optimization model of a biochemical detection micromixer based on RSM and MOEA\/D. Chem Eng Process Process Intensif 173:108832","journal-title":"Chem Eng Process Process Intensif"},{"key":"9746_CR21","doi-asserted-by":"crossref","first-page":"592","DOI":"10.1016\/j.ins.2021.07.048","volume":"578","author":"R Jiao","year":"2021","unstructured":"Jiao R, Zeng S, Li C, Ong Y-S (2021) Two-type weight adjustments in MOEA\/D for highly constrained many-objective optimization. Inf Sci 578:592\u2013614","journal-title":"Inf Sci"},{"issue":"1","key":"9746_CR22","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1007\/s10845-015-1087-8","volume":"29","author":"Q Fan","year":"2018","unstructured":"Fan Q, Yan X (2018) Multi-objective modified differential evolution algorithm with archive-base mutation for solving multi-objective $$ p $$ p-xylene oxidation process. J Intell Manuf 29(1):35\u201349","journal-title":"J Intell Manuf"},{"issue":"2","key":"9746_CR23","doi-asserted-by":"crossref","first-page":"284","DOI":"10.1109\/TEVC.2008.925798","volume":"13","author":"H Li","year":"2008","unstructured":"Li H, Zhang Q (2008) Multiobjective optimization problems with complicated Pareto sets, MOEA\/D and NSGA-II. IEEE Trans Evol Comput 13(2):284\u2013302","journal-title":"IEEE Trans Evol Comput"},{"key":"9746_CR24","doi-asserted-by":"crossref","unstructured":"Zhang Q, Liu W, Li H (2009) The performance of a new version of MOEA\/D on CEC09 unconstrained MOP test instances, In: 2009 IEEE congress on evolutionary computation, pp. 203\u2013208: IEEE.","DOI":"10.1109\/CEC.2009.4982949"},{"issue":"6","key":"9746_CR25","doi-asserted-by":"crossref","first-page":"1845","DOI":"10.1109\/TSMCB.2012.2231860","volume":"43","author":"L Ke","year":"2013","unstructured":"Ke L, Zhang Q, Battiti R (2013) MOEA\/D-ACO: A multiobjective evolutionary algorithm using decomposition and antcolony. IEEE Trans Cybern 43(6):1845\u20131859","journal-title":"IEEE Trans Cybern"},{"issue":"3","key":"9746_CR26","doi-asserted-by":"crossref","first-page":"456","DOI":"10.1109\/TEVC.2009.2033671","volume":"14","author":"Q Zhang","year":"2009","unstructured":"Zhang Q, Liu W, Tsang E, Virginas B (2009) Expensive multiobjective optimization by MOEA\/D with Gaussian process model. IEEE Trans Evol Comput 14(3):456\u2013474","journal-title":"IEEE Trans Evol Comput"},{"key":"9746_CR27","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1016\/j.swevo.2019.02.003","volume":"46","author":"H Li","year":"2019","unstructured":"Li H, Deb K, Zhang Q, Suganthan PN, Chen L (2019) Comparison between MOEA\/D and NSGA-III on a set of novel many and multi-objective benchmark problems with challenging difficulties. Swarm Evol Comput 46:104\u2013117","journal-title":"Swarm Evol Comput"},{"key":"9746_CR28","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.ins.2020.02.066","volume":"522","author":"Y Zhang","year":"2020","unstructured":"Zhang Y, Wang G-G, Li K, Yeh W-C, Jian M, Dong J (2020) Enhancing MOEA\/D with information feedback models for large-scale many-objective optimization. Inf Sci 522:1\u201316","journal-title":"Inf Sci"},{"key":"9746_CR29","doi-asserted-by":"crossref","unstructured":"Peng W, Zhang Q (2008) A decomposition-based multi-objective particle swarm optimization algorithm for continuous optimization problems, In: 2008 IEEE international conference on granular computing, pp. 534\u2013537: IEEE.","DOI":"10.1109\/GRC.2008.4664724"},{"issue":"10","key":"9746_CR30","doi-asserted-by":"crossref","first-page":"3057","DOI":"10.1016\/j.solener.2012.07.014","volume":"86","author":"H Nasiraghdam","year":"2012","unstructured":"Nasiraghdam H, Jadid S (2012) Optimal hybrid PV\/WT\/FC sizing and distribution system reconfiguration using multi-objective artificial bee colony (MOABC) algorithm. Sol Energy 86(10):3057\u20133071","journal-title":"Sol Energy"},{"key":"9746_CR31","unstructured":"Zitzler E, Laumanns M, Thiele L (2001) SPEA2: Improving the strength Pareto evolutionary algorithm. TIK Report 103"},{"key":"9746_CR32","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1016\/j.asoc.2015.03.003","volume":"31","author":"SA Uymaz","year":"2015","unstructured":"Uymaz SA, Tezel G, Yel E (2015) Artificial algae algorithm (AAA) for nonlinear global optimization. Appl Soft Comput 31:153\u2013171","journal-title":"Appl Soft Comput"},{"key":"9746_CR33","doi-asserted-by":"crossref","unstructured":"Clerc M (2011) Standard particle swarm optimisation from 2006 to 2011, Particle Swarm Central, 253","DOI":"10.1002\/9780470612163"},{"issue":"3","key":"9746_CR34","doi-asserted-by":"crossref","first-page":"6915","DOI":"10.4249\/scholarpedia.6915","volume":"5","author":"D Karaboga","year":"2010","unstructured":"Karaboga D (2010) Artificial bee colony algorithm. Scholarpedia 5(3):6915","journal-title":"Scholarpedia"},{"issue":"3","key":"9746_CR35","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1504\/IJBIC.2013.055093","volume":"5","author":"X-S Yang","year":"2013","unstructured":"Yang X-S, He X (2013) Bat algorithm: literature review and applications. Int J Bio-inspired Comput 5(3):141\u2013149","journal-title":"Int J Bio-inspired Comput"},{"key":"9746_CR36","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1023\/A:1008202821328","volume":"11","author":"R Storn","year":"1997","unstructured":"Storn R, Price K (1997) Differential evolution\u2013a simple and efficient heuristic for global optimization over continuous spaces. J Global Optim 11:341\u2013359","journal-title":"J Global Optim"},{"issue":"1","key":"9746_CR37","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1109\/4235.585893","volume":"1","author":"DH Wolpert","year":"1997","unstructured":"Wolpert DH, Macready WG (1997) No free lunch theorems for optimization. IEEE Trans Evol Comput 1(1):67\u201382","journal-title":"IEEE Trans Evol Comput"},{"key":"9746_CR38","doi-asserted-by":"crossref","first-page":"112187","DOI":"10.1016\/j.engstruct.2021.112187","volume":"239","author":"DE Vargas","year":"2021","unstructured":"Vargas DE, Lemonge AC, Barbosa HJ, Bernardino HS (2021) Solving multi-objective structural optimization problems using GDE3 and NSGA-II with reference points. Eng Struct 239:112187","journal-title":"Eng Struct"},{"key":"9746_CR39","doi-asserted-by":"crossref","first-page":"106856","DOI":"10.1016\/j.knosys.2021.106856","volume":"218","author":"M Premkumar","year":"2021","unstructured":"Premkumar M, Jangir P, Sowmya R (2021) MOGBO: A new multiobjective gradient-based optimizer for real-world structural optimization problems. Knowl-Based Syst 218:106856","journal-title":"Knowl-Based Syst"},{"key":"9746_CR40","doi-asserted-by":"crossref","first-page":"109738","DOI":"10.1016\/j.chaos.2020.109738","volume":"135","author":"J-S Chou","year":"2020","unstructured":"Chou J-S, Truong D-N (2020) Multiobjective optimization inspired by behavior of jellyfish for solving structural design problems. Chaos, Solitons Fractals 135:109738","journal-title":"Chaos, Solitons Fractals"},{"key":"9746_CR41","doi-asserted-by":"crossref","first-page":"430","DOI":"10.1016\/j.eswa.2017.09.051","volume":"92","author":"V Ho-Huu","year":"2018","unstructured":"Ho-Huu V, Hartjes S, Visser HG, Curran R (2018) An improved MOEA\/D algorithm for bi-objective optimization problems with complex Pareto fronts and its application to structural optimization. Expert Syst Appl 92:430\u2013446","journal-title":"Expert Syst Appl"},{"issue":"11\u201312","key":"9746_CR42","doi-asserted-by":"crossref","first-page":"1135","DOI":"10.1080\/01457632.2016.1217064","volume":"38","author":"L Zhao","year":"2017","unstructured":"Zhao L et al (2017) Multi-objective optimization analysis of structural design for large cooling towers. Heat Transfer Eng 38(11\u201312):1135\u20131145","journal-title":"Heat Transfer Eng"},{"key":"9746_CR43","doi-asserted-by":"crossref","unstructured":"Hughes O, Ma M, Paik JK (2014) Applications of vector evaluated genetic algorithms (VEGA) in ultimate limit state based ship structural design, In: International conference on offshore mechanics and arctic engineering, vol. 45493, p. V007T12A006: American Society of Mechanical Engineers.","DOI":"10.1115\/OMAE2014-23379"},{"issue":"2","key":"9746_CR44","doi-asserted-by":"crossref","first-page":"021005","DOI":"10.1115\/1.4048010","volume":"18","author":"X Liao","year":"2021","unstructured":"Liao X et al (2021) A framework of optimal design of thermal management system for lithium-ion battery pack using multi-objectives optimization. J Electrochem Energy Conv Storage 18(2):021005","journal-title":"J Electrochem Energy Conv Storage"},{"key":"9746_CR45","unstructured":"Bekda\u015f G, Nigdeli M, Y\u00fccel M, Kayabekir A (2021) Yapay Zeka Optimizasyon Algoritmalar\u0131 ve M\u00fchendislik Uygulamalar\u0131, Se\u00e7kin Yay\u0131nc\u0131l\u0131k, Ankara"},{"key":"9746_CR46","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1016\/j.istruc.2022.04.020","volume":"40","author":"M Y\u00fccel","year":"2022","unstructured":"Y\u00fccel M, Nigdeli SM, Bekda\u015f G (2022) Generation of sustainable models with multi-objective optimum design of reinforced concrete (RC) structures. Structures 40:223\u2013236","journal-title":"Structures"},{"key":"9746_CR47","doi-asserted-by":"crossref","first-page":"105631","DOI":"10.1016\/j.asoc.2019.105631","volume":"83","author":"H Afshari","year":"2019","unstructured":"Afshari H, Hare W, Tesfamariam S (2019) Constrained multi-objective optimization algorithms: Review and comparison with application in reinforced concrete structures. Appl Soft Comput 83:105631","journal-title":"Appl Soft Comput"},{"issue":"15","key":"9746_CR48","doi-asserted-by":"crossref","first-page":"11689","DOI":"10.3390\/su151511689","volume":"15","author":"P Jelu\u0161i\u010d","year":"2023","unstructured":"Jelu\u0161i\u010d P, \u017dula T (2023) Sustainable design of circular reinforced concrete column sections via multi-objective optimization. Sustainability 15(15):11689","journal-title":"Sustainability"},{"issue":"12","key":"9746_CR49","doi-asserted-by":"crossref","first-page":"2011","DOI":"10.1080\/0305215X.2019.1693554","volume":"52","author":"AM Martins","year":"2020","unstructured":"Martins AM, Sim\u00f5es LM, Negr\u00e3o JH, Lopes AV (2020) Sensitivity analysis and optimum design of reinforced concrete frames according to Eurocode 2. Eng Optim 52(12):2011\u20132032","journal-title":"Eng Optim"},{"key":"9746_CR50","doi-asserted-by":"crossref","unstructured":"Pareto V (1964) Cours d'\u00e9conomie politique. Librairie Droz","DOI":"10.3917\/droz.paret.1964.01"},{"issue":"20","key":"9746_CR51","doi-asserted-by":"crossref","first-page":"6329","DOI":"10.1080\/00207543.2022.2044537","volume":"60","author":"I Khettabi","year":"2022","unstructured":"Khettabi I, Benyoucef L, Amine Boutiche M (2022) Sustainable multi-objective process planning in reconfigurable manufacturing environment: adapted new dynamic NSGA-II vs New NSGA-III. Int J Prod Res 60(20):6329\u20136349","journal-title":"Int J Prod Res"},{"key":"9746_CR52","doi-asserted-by":"crossref","first-page":"106226","DOI":"10.1016\/j.engfailanal.2022.106226","volume":"136","author":"Z Zheng","year":"2022","unstructured":"Zheng Z, Lin J, Hu Y, Zhou Q, Yi C (2022) Dynamic unbalance identification and quantitative diagnosis of cardan shaft in high-speed train based on improved TQWT-RBFNN-NSGA-II method. Eng Fail Anal 136:106226","journal-title":"Eng Fail Anal"},{"key":"9746_CR53","doi-asserted-by":"crossref","first-page":"101818","DOI":"10.1016\/j.csite.2022.101818","volume":"31","author":"L Bao","year":"2022","unstructured":"Bao L, Zheng M, Zhou Q, Gao P, Xu Y, Jiang H (2022) Multi-objective optimization of partition temperature of steel sheet by NSGA-II using response surface methodology. Case Stud Therm Eng 31:101818","journal-title":"Case Stud Therm Eng"},{"key":"9746_CR54","doi-asserted-by":"crossref","unstructured":"Tombak GI, G\u00fczelhan \u015eN, Afacan E, D\u00fcndar G (2022) Simulated annealing assisted NSGA-III-based multi-objective analog IC sizing tool. Integration","DOI":"10.1016\/j.vlsi.2022.02.009"},{"key":"9746_CR55","doi-asserted-by":"crossref","first-page":"108931","DOI":"10.1016\/j.anucene.2021.108931","volume":"169","author":"J Xu","year":"2022","unstructured":"Xu J, Tang H, Wang X, Qin G, Jin X, Li D (2022) NSGA-II algorithm-based LQG controller design for nuclear reactor power control. Ann Nucl Energy 169:108931","journal-title":"Ann Nucl Energy"},{"issue":"3","key":"9746_CR56","first-page":"440","volume":"21","author":"A Trivedi","year":"2016","unstructured":"Trivedi A, Srinivasan D, Sanyal K, Ghosh A (2016) A survey of multiobjective evolutionary algorithms based on decomposition. IEEE Trans Evol Comput 21(3):440\u2013462","journal-title":"IEEE Trans Evol Comput"},{"key":"9746_CR57","unstructured":"Canter-Lund H, Lund JW (1995) Freshwater algae: their microscopic world explored. Bristol: Biopress 582"},{"issue":"2","key":"9746_CR58","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1162\/106365600568202","volume":"8","author":"E Zitzler","year":"2000","unstructured":"Zitzler E, Deb K, Thiele L (2000) Comparison of multiobjective evolutionary algorithms: Empirical results. Evol Comput 8(2):173\u2013195","journal-title":"Evol Comput"},{"key":"9746_CR59","unstructured":"Deb K, Thiele L, Laumanns M, Zitzler E (2005) Scalable test problems for evolutionary multiobjective optimization, In: Evolutionary Multiobjective Optimization: teoretical advances and applications. London Springer London, pp. 105\u2013145"},{"issue":"5","key":"9746_CR60","doi-asserted-by":"crossref","first-page":"477","DOI":"10.1109\/TEVC.2005.861417","volume":"10","author":"S Huband","year":"2006","unstructured":"Huband S, Hingston P, Barone L, While L (2006) A review of multiobjective test problems and a scalable test problem toolkit. IEEE Trans Evol Comput 10(5):477\u2013506","journal-title":"IEEE Trans Evol Comput"},{"issue":"1","key":"9746_CR61","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1109\/3468.650319","volume":"28","author":"CM Fonseca","year":"1998","unstructured":"Fonseca CM, Fleming PJ (1998) Multiobjective optimization and multiple constraint handling with evolutionary algorithms. I. A unified formulation. IEEE Trans Syst Man Cybern-Part A Syst Humans 28(1):26\u201337","journal-title":"IEEE Trans Syst Man Cybern-Part A Syst Humans"},{"key":"9746_CR62","doi-asserted-by":"crossref","unstructured":"Kursawe F (1990) A variant of evolution strategies for vector optimization, In: International conference on parallel problem solving from nature, pp. 193\u2013197: Springer.","DOI":"10.1007\/BFb0029752"},{"key":"9746_CR63","unstructured":"Schaffer JD (1985) Multiple objective optimization with vector evaluated genetic algorithms, In: Proceedings of the first international conference on genetic algorithms and their applications, Lawrence Erlbaum Associates. Inc., Publishers."},{"issue":"2","key":"9746_CR64","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1080\/00207729608929211","volume":"27","author":"R Vlennet","year":"1996","unstructured":"Vlennet R, Fonteix C, Marc I (1996) Multicriteria optimization using a genetic algorithm for determining a Pareto set. Int J Syst Sci 27(2):255\u2013260","journal-title":"Int J Syst Sci"},{"issue":"10","key":"9746_CR65","doi-asserted-by":"crossref","first-page":"760","DOI":"10.1016\/j.advengsoft.2011.05.014","volume":"42","author":"JJ Durillo","year":"2011","unstructured":"Durillo JJ, Nebro AJ (2011) jMetal: A Java framework for multi-objective optimization. Adv Eng Softw 42(10):760\u2013771","journal-title":"Adv Eng Softw"},{"key":"9746_CR66","doi-asserted-by":"crossref","unstructured":"Biswas S, Das S, Suganthan PN, Coello CAC (2014) Evolutionary multiobjective optimization in dynamic environments: A set of novel benchmark functions, In: 2014 IEEE congress on evolutionary computation (CEC), pp. 3192\u20133199: IEEE.","DOI":"10.1109\/CEC.2014.6900487"},{"key":"9746_CR67","unstructured":"Nigdeli SM, Bekda\u015f G, Yang X-S (2016) Application of the flower pollination algorithm in structural engineering, In: Metaheuristics and optimization in civil engineering. Springer, pp. 25\u201342."},{"key":"9746_CR68","unstructured":"Committee A (2008), Building code requirements for structural concrete (ACI 318\u201308) and commentary, American Concrete Institute."},{"key":"9746_CR69","unstructured":"Anonymous (2023, 5.18.2023) Karakod: The price of one cubic meter of concrete. Available: https:\/\/www.karekod.org\/blog\/hazir-beton-fiyatlari-2023\/"},{"key":"9746_CR70","unstructured":"Anonymous (2023, 5\/18\/2023) S&P Global: 1 ton steel price May, 2023 Available: https:\/\/www.spglobal.com\/commodityinsights\/en\/our-methodology\/price-assessments\/metals\/turkish-rebar-export-price-explained"},{"key":"9746_CR71","unstructured":"Anonymous (2023, 5.18.2023) Demirfiyatlari.com:1 ton steel price May, 2023 Available:https:\/\/www.demirfiyatlari.com\/"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-024-09746-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-024-09746-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-024-09746-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,21]],"date-time":"2024-11-21T21:41:58Z","timestamp":1732225318000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-024-09746-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,6,14]]},"references-count":71,"journal-issue":{"issue":"28","published-print":{"date-parts":[[2024,10]]}},"alternative-id":["9746"],"URL":"https:\/\/doi.org\/10.1007\/s00521-024-09746-3","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,6,14]]},"assertion":[{"value":"21 May 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 March 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 June 2024","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 interests"}}]}}