{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T07:35:19Z","timestamp":1770708919972,"version":"3.49.0"},"reference-count":111,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2024,1,17]],"date-time":"2024-01-17T00:00:00Z","timestamp":1705449600000},"content-version":"vor","delay-in-days":20,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,12,28]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Dynamic differential annealed optimization (DDAO) is a recently developed physics-based metaheuristic technique that mimics the classical simulated annealing mechanism. However, DDAO has limited search abilities, especially when solving complicated and complex problems. A unique variation of DDAO, dubbed as mDDAO, is developed in this study, in which opposition-based learning technique and a novel updating equation\u00a0are combined with DDAO. mDDAO is tested on 10 different functions from CEC2020 and compared with the original DDAO and nine other algorithms. The proposed mDDAO algorithm performance is evaluated using 10 numerical constrained functions from the recently released CEC 2020 benchmark suite, which includes a variety of dimensionally challenging optimisation tasks. Furthermore, to measure its viability, mDDAO is employed to solve feature selection problems using fourteen UCI datasets and a real-life Lymphoma diagnosis problem. Results prove that mDDAO has a superior performance and consistently outperforms counterparts across benchmarks, achieving fitness improvements ranging from 1% to 99.99%. In feature selection, mDDAO excels by reducing feature count by 23% to 79% compared to other methods, enhancing computational efficiency and maintaining classification accuracy. Moreover, in lymphoma diagnosis, mDDAO demonstrates up to 54% higher average fitness, 18% accuracy improvement, and 86% faster computation times.<\/jats:p>","DOI":"10.1093\/jcde\/qwad108","type":"journal-article","created":{"date-parts":[[2024,1,18]],"date-time":"2024-01-18T17:36:22Z","timestamp":1705599382000},"page":"49-72","source":"Crossref","is-referenced-by-count":6,"title":["An enhanced dynamic differential annealed algorithm for global optimization and feature selection"],"prefix":"10.1093","volume":"11","author":[{"given":"Abdelazim G","family":"Hussien","sequence":"first","affiliation":[{"name":"Department of Computer and Information Science , Link\u00f6ping University, 581 83 Link\u00f6ping , Sweden"},{"name":"Faculty of Science, Fayoum University , 63514 Faiyum , Egypt"},{"name":"Applied Science Research Center, Applied Science Private University , Amman 11931 , Jordan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sumit","family":"Kumar","sequence":"additional","affiliation":[{"name":"Australian Maritime College, College of Sciences and Engineering, University of Tasmania , 7248 Launceston , Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Simrandeep","family":"Singh","sequence":"additional","affiliation":[{"name":"Department of Electronics & Communication Engineering , UCRD, Chandigarh University, Gharuan, Punjab 160036 , India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3128-9025","authenticated-orcid":false,"given":"Jeng-Shyang","family":"Pan","sequence":"additional","affiliation":[{"name":"College of Computer Science and Engineering, Shandong University of Science and Technology , 266590 Qingdao , China"},{"name":"Department of Information Management, Chaoyang University of Technology , 41349 Taichung , Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fatma A","family":"Hashim","sequence":"additional","affiliation":[{"name":"Faculty of Engineering, Helwan University , Cairo 11795 , Egypt"},{"name":"MEU Research Unit, Middle East University , Amman 11831 , Jordan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2024,1,17]]},"reference":[{"key":"2024030113560794200_bib5","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-030-10674-4","volume-title":"Feature Selection and Enhanced Krill Herd Algorithm for Text Document Clustering","author":"Abualigah","year":"2019"},{"key":"2024030113560794200_bib1","doi-asserted-by":"crossref","first-page":"345","DOI":"10.3390\/a13120345","article-title":"Nature-inspired optimization algorithms for text document clustering\u2019a comprehensive analysis","volume":"13","author":"Abualigah","year":"2020","journal-title":"Algorithms"},{"key":"2024030113560794200_bib2","doi-asserted-by":"crossref","first-page":"113609","DOI":"10.1016\/j.cma.2020.113609","article-title":"The arithmetic optimization algorithm","volume":"376","author":"Abualigah","year":"2021","journal-title":"Computer Methods in Applied Mechanics and Engineering"},{"key":"2024030113560794200_bib3","doi-asserted-by":"crossref","first-page":"116158","DOI":"10.1016\/j.eswa.2021.116158","article-title":"Reptile search algorithm (rsa): A nature-inspired meta-heuristic optimizer","volume":"191","author":"Abualigah","year":"2022","journal-title":"Expert Systems with Applications"},{"key":"2024030113560794200_bib4","first-page":"1","article-title":"Improved prairie dog optimization algorithm by dwarf mongoose optimization algorithm for optimization problems","author":"Abualigah","year":"2023","journal-title":"Multimedia Tools and Applications"},{"key":"2024030113560794200_bib6","doi-asserted-by":"crossref","first-page":"116516","DOI":"10.1016\/j.eswa.2022.116516","article-title":"Info: An efficient optimization algorithm based on weighted mean of vectors","volume":"195","author":"Ahmadianfar","year":"2022","journal-title":"Expert Systems with Applications"},{"key":"2024030113560794200_bib7","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1007\/s10462-016-9486-6","article-title":"Plant intelligence based metaheuristic optimization algorithms","volume":"47","author":"Akyol","year":"2017","journal-title":"Artificial Intelligence Review"},{"key":"2024030113560794200_bib8","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s44196-023-00279-6","article-title":"Artificial ecosystem-based optimization with dwarf mongoose optimization for feature selection and global optimization problems","volume":"16","author":"Al-Shourbaji","year":"2023","journal-title":"International Journal of Computational Intelligence Systems"},{"key":"2024030113560794200_bib9","doi-asserted-by":"crossref","first-page":"39496","DOI":"10.1109\/ACCESS.2019.2906757","article-title":"Binary optimization using hybrid grey wolf optimization for feature selection","volume":"7","author":"Al-Tashi","year":"2019","journal-title":"IEEE Access"},{"key":"2024030113560794200_bib10","doi-asserted-by":"crossref","first-page":"51","DOI":"10.33383\/2019-029","article-title":"Comparative assessment of light-based intelligent search and optimization algorithms","volume":"28","author":"Alatas","year":"2020","journal-title":"Light & Engineering"},{"key":"2024030113560794200_bib11","doi-asserted-by":"crossref","first-page":"26343","DOI":"10.1109\/ACCESS.2019.2897325","article-title":"A new hybrid algorithm based on grey wolf optimization and crow search algorithm for unconstrained function optimization and feature selection","volume":"7","author":"Arora","year":"2019","journal-title":"IEEE Access"},{"key":"2024030113560794200_bib12","doi-asserted-by":"crossref","first-page":"25073","DOI":"10.1109\/ACCESS.2022.3153493","article-title":"War strategy optimization algorithm: a new effective metaheuristic algorithm for global optimization","volume":"10","author":"Ayyarao","year":"2022","journal-title":"IEEE Access"},{"key":"2024030113560794200_bib13","doi-asserted-by":"crossref","first-page":"111081","DOI":"10.1016\/j.knosys.2023.111081","article-title":"A sinh cosh optimizer","volume":"282","author":"Bai","year":"2023","journal-title":"Knowledge-Based Systems"},{"key":"2024030113560794200_bib14","doi-asserted-by":"crossref","first-page":"268","DOI":"10.1145\/937503.937505","article-title":"Metaheuristics in combinatorial optimization: Overview and conceptual comparison","volume":"35","author":"Blum","year":"2003","journal-title":"ACM Computing Surveys (CSUR)"},{"key":"2024030113560794200_bib15","doi-asserted-by":"crossref","first-page":"117118","DOI":"10.1016\/j.eswa.2022.117118","article-title":"Poplar optimization algorithm: a new meta-heuristic optimization technique for numerical optimization and image segmentation","volume":"200","author":"Chen","year":"2022","journal-title":"Expert Systems with Applications"},{"key":"2024030113560794200_bib16","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1016\/j.aej.2022.12.045","article-title":"Improved bald eagle search algorithm for global optimization and feature selection","volume":"68","author":"Chhabra","year":"2023","journal-title":"Alexandria Engineering Journal"},{"key":"2024030113560794200_bib17","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1007\/978-3-319-93073-2_11","article-title":"Performance and limitations of metaheuristics","volume-title":"An Introduction to Metaheuristics for Optimization","author":"Chopard","year":"2018"},{"key":"2024030113560794200_bib18","doi-asserted-by":"crossref","first-page":"14591","DOI":"10.1038\/s41598-023-41608-1","article-title":"A leader supply-demand-based optimization for large scale optimal power flow problem considering renewable energy generations","volume":"13","author":"Daqaq","year":"2023","journal-title":"Scientific Reports"},{"key":"2024030113560794200_bib19","doi-asserted-by":"crossref","first-page":"20281","DOI":"10.1109\/ACCESS.2019.2897580","article-title":"An improved ant colony optimization algorithm based on hybrid strategies for scheduling problem","volume":"7","author":"Deng","year":"2019","journal-title":"IEEE Access"},{"key":"2024030113560794200_bib20","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1016\/j.knosys.2018.11.024","article-title":"Seagull optimization algorithm: Theory and its applications for large-scale industrial engineering problems","volume":"165","author":"Dhiman","year":"2019","journal-title":"Knowledge-Based Systems"},{"key":"2024030113560794200_bib21","doi-asserted-by":"crossref","first-page":"106040","DOI":"10.1016\/j.cie.2019.106040","article-title":"A survey on new generation metaheuristic algorithms","volume":"137","author":"Dokeroglu","year":"2019","journal-title":"Computers & Industrial Engineering"},{"key":"2024030113560794200_bib22","doi-asserted-by":"crossref","first-page":"122054","DOI":"10.1016\/j.apenergy.2023.122054","article-title":"Single and multi-objectives based on an improved golden jackal optimization algorithm for simultaneous integration of multiple capacitors and multi-type dgs in distribution systems","volume":"353","author":"Elseify","year":"2024","journal-title":"Applied Energy"},{"key":"2024030113560794200_bib23","doi-asserted-by":"crossref","first-page":"156","DOI":"10.1016\/j.eswa.2018.06.023","article-title":"Improved grasshopper optimization algorithm using opposition-based learning","volume":"112","author":"Ewees","year":"2018","journal-title":"Expert Systems with Applications"},{"key":"2024030113560794200_bib24","doi-asserted-by":"crossref","first-page":"105190","DOI":"10.1016\/j.knosys.2019.105190","article-title":"Equilibrium optimizer: A novel optimization algorithm","volume":"191","author":"Faramarzi","year":"2020","journal-title":"Knowledge-Based Systems"},{"key":"2024030113560794200_bib25","doi-asserted-by":"crossref","first-page":"652","DOI":"10.1016\/j.apm.2017.10.001","article-title":"A new hybrid algorithm for continuous optimization problem","volume":"55","author":"Farnad","year":"2018","journal-title":"Applied Mathematical Modelling"},{"key":"2024030113560794200_bib26","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2019\/2361282","article-title":"An improved grey wolf optimization algorithm with variable weights","volume":"2019","author":"Gao","year":"2019","journal-title":"Computational Intelligence and Neuroscience"},{"key":"2024030113560794200_bib27","doi-asserted-by":"crossref","first-page":"106392","DOI":"10.1016\/j.asoc.2020.106392","article-title":"Dynamic differential annealed optimization: New metaheuristic optimization algorithm for engineering applications","volume":"93","author":"Ghafil","year":"2020","journal-title":"Applied Soft Computing"},{"key":"2024030113560794200_bib28","volume-title":"Handbook of Metaheuristics","author":"Glover","year":"2006"},{"key":"2024030113560794200_bib29","doi-asserted-by":"crossref","first-page":"108320","DOI":"10.1016\/j.knosys.2022.108320","article-title":"Snake optimizer: A novel meta-heuristic optimization algorithm","volume":"242","author":"Hashim","year":"2022","journal-title":"Knowledge-Based Systems"},{"key":"2024030113560794200_bib30","doi-asserted-by":"crossref","first-page":"110146","DOI":"10.1016\/j.knosys.2022.110146","article-title":"Fick\u2019s law algorithm: A physical law-based algorithm for numerical optimization","volume":"260","author":"Hashim","year":"2023","journal-title":"Knowledge-Based Systems"},{"key":"2024030113560794200_bib31","doi-asserted-by":"crossref","DOI":"10.1049\/gtd2.12879","article-title":"An enhanced hunter-prey optimization for optimal power flow with facts devices and wind power integration","author":"Hassan","year":"2023","journal-title":"IET Generation, Transmission & Distribution"},{"key":"2024030113560794200_bib32","doi-asserted-by":"crossref","DOI":"10.1049\/gtd2.12892","article-title":"Supply-demand optimizer for economic emission dispatch incorporating price penalty factor and variable load demand levels","author":"Hassan","year":"2023","journal-title":"IET Generation, Transmission & Distribution"},{"key":"2024030113560794200_bib33","doi-asserted-by":"crossref","DOI":"10.1201\/9781315222455","volume-title":"Swarm Intelligence: Principles, Advances, and Applications","author":"Hassanien","year":"2018"},{"key":"2024030113560794200_bib34","first-page":"770","article-title":"Deep residual learning for image recognition","volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","author":"He","year":"2016"},{"key":"2024030113560794200_bib35","doi-asserted-by":"crossref","first-page":"849","DOI":"10.1016\/j.future.2019.02.028","article-title":"Harris hawks optimization: Algorithm and applications","volume":"97","author":"Heidari","year":"2019","journal-title":"Future Generation Computer Systems"},{"key":"2024030113560794200_bib36","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1007\/BF02239976","article-title":"Using tabu search techniques for graph coloring","volume":"39","author":"Hertz","year":"1987","journal-title":"Computing"},{"key":"2024030113560794200_bib37","doi-asserted-by":"crossref","first-page":"103731","DOI":"10.1016\/j.engappai.2020.103731","article-title":"L\u00e9vy flight distribution: A new metaheuristic algorithm for solving engineering optimization problems","volume":"94","author":"Houssein","year":"2020","journal-title":"Engineering Applications of Artificial Intelligence"},{"key":"2024030113560794200_bib38","doi-asserted-by":"crossref","first-page":"107348","DOI":"10.1016\/j.knosys.2021.107348","article-title":"An improved opposition-based marine predators algorithm for global optimization and multilevel thresholding image segmentation","volume":"229","author":"Houssein","year":"2021","journal-title":"Knowledge-Based Systems"},{"key":"2024030113560794200_bib39","doi-asserted-by":"crossref","first-page":"107389","DOI":"10.1016\/j.compbiomed.2023.107389","article-title":"Liver cancer algorithm: A novel bio-inspired optimizer","volume":"165","author":"Houssein","year":"2023","journal-title":"Computers in Biology and Medicine"},{"key":"2024030113560794200_bib43","doi-asserted-by":"crossref","first-page":"874","DOI":"10.1109\/TCYB.2020.3015756","article-title":"Multiobjective particle swarm optimization for feature selection with fuzzy cost","volume":"51","author":"Hu","year":"2020","journal-title":"IEEE Transactions on Cybernetics"},{"key":"2024030113560794200_bib41","article-title":"Chaotic diffusion-limited aggregation enhanced grey wolf optimizer: Insights, analysis, binarization, and feature selection","volume":"37","author":"Hu","year":"2021","journal-title":"International Journal of Intelligent Systems"},{"key":"2024030113560794200_bib42","doi-asserted-by":"crossref","first-page":"107761","DOI":"10.1016\/j.knosys.2021.107761","article-title":"Dispersed foraging slime mould algorithm: Continuous and binary variants for global optimization and wrapper-based feature selection","volume":"237","author":"Hu","year":"2022","journal-title":"Knowledge-Based Systems"},{"key":"2024030113560794200_bib40","doi-asserted-by":"crossref","first-page":"851","DOI":"10.3390\/math11040851","article-title":"Ejs: Multi-strategy enhanced jellyfish search algorithm for engineering applications","volume":"11","author":"Hu","year":"2023","journal-title":"Mathematics"},{"key":"2024030113560794200_bib44","first-page":"1","article-title":"An enhanced opposition-based salp swarm algorithm for global optimization and engineering problems","volume":"13","author":"Hussien","year":"2021","journal-title":"Journal of Ambient Intelligence and Humanized Computing"},{"key":"2024030113560794200_bib45","first-page":"1","article-title":"A self-adaptive harris hawks optimization algorithm with opposition-based learning and chaotic local search strategy for global optimization and feature selection","volume":"13","author":"Hussien","year":"2021","journal-title":"International Journal of Machine Learning and Cybernetics"},{"key":"2024030113560794200_bib46","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1109\/INTELCIS.2017.8260031","article-title":"A binary whale optimization algorithm with hyperbolic tangent fitness function for feature selection","volume-title":"2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS)","author":"Hussien","year":"2017"},{"key":"2024030113560794200_bib47","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1007\/978-981-10-8863-6_9","article-title":"S-shaped binary whale optimization algorithm for feature selection","volume-title":"Recent Trends in Signal and Image Processing","author":"Hussien","year":"2019"},{"key":"2024030113560794200_bib48","doi-asserted-by":"crossref","first-page":"173548","DOI":"10.1109\/ACCESS.2020.3024108","article-title":"Crow search algorithm: theory, recent advances, and applications","volume":"8","author":"Hussien","year":"2020","journal-title":"IEEE Access"},{"key":"2024030113560794200_bib49","doi-asserted-by":"crossref","first-page":"945","DOI":"10.1080\/0305215X.2019.1624740","article-title":"New binary whale optimization algorithm for discrete optimization problems","volume":"52","author":"Hussien","year":"2020","journal-title":"Engineering Optimization"},{"key":"2024030113560794200_bib50","doi-asserted-by":"crossref","first-page":"2254","DOI":"10.3390\/pr10112254","article-title":"An enhanced evaporation rate water-cycle algorithm for global optimization","volume":"10","author":"Hussien","year":"2022","journal-title":"Processes"},{"key":"2024030113560794200_bib51","doi-asserted-by":"crossref","first-page":"3155","DOI":"10.1007\/s12652-018-1031-9","article-title":"Improved salp swarm algorithm based on particle swarm optimization for feature selection","volume":"10","author":"Ibrahim","year":"2019","journal-title":"Journal of Ambient Intelligence and Humanized Computing"},{"key":"2024030113560794200_bib52","doi-asserted-by":"crossref","first-page":"e0291788","DOI":"10.1371\/journal.pone.0291788","article-title":"An elite approach to re-design aquila optimizer for efficient afr system control","volume":"18","author":"Izci","year":"2023","journal-title":"Plos one"},{"key":"2024030113560794200_bib53","first-page":"qwad048","article-title":"An improved reptile search algorithm with ghost opposition-based learning for global optimization problems","author":"Jia","year":"2023","journal-title":"Journal of Computational Design and Engineering"},{"key":"2024030113560794200_bib54","doi-asserted-by":"crossref","first-page":"107224","DOI":"10.1016\/j.cie.2021.107224","article-title":"Flow direction algorithm (fda): A novel optimization approach for solving optimization problems","volume":"156","author":"Karami","year":"2021","journal-title":"Computers & Industrial Engineering"},{"key":"2024030113560794200_bib55","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/j.advengsoft.2017.03.014","article-title":"A novel meta-heuristic optimization algorithm: thermal exchange optimization","volume":"110","author":"Kaveh","year":"2017","journal-title":"Advances in Engineering Software"},{"key":"2024030113560794200_bib56","doi-asserted-by":"crossref","first-page":"1699","DOI":"10.1007\/s00500-017-2894-y","article-title":"An efficient hybrid algorithm based on water cycle and moth-flame optimization algorithms for solving numerical and constrained engineering optimization problems","volume":"23","author":"Khalilpourazari","year":"2019","journal-title":"Soft Computing"},{"key":"2024030113560794200_bib57","first-page":"1","article-title":"Radial basis function trained with dynamic differential annealed optimization algorithm based maximum power point tracking control of pv system under uniform and non-uniform irradiance","volume-title":"2021 International Conference on Emerging Power Technologies (ICEPT)","author":"Khan","year":"2021"},{"key":"2024030113560794200_bib58","doi-asserted-by":"crossref","first-page":"104343","DOI":"10.1016\/j.est.2022.104343","article-title":"An improved arithmetic optimization algorithm for design of a microgrid with energy storage system: Case study of el kharga oasis, egypt","volume":"51","author":"Kharrich","year":"2022","journal-title":"Journal of Energy Storage"},{"key":"2024030113560794200_bib59","doi-asserted-by":"crossref","first-page":"113338","DOI":"10.1016\/j.eswa.2020.113338","article-title":"Chimp optimization algorithm","volume":"149","author":"Khishe","year":"2020","journal-title":"Expert Systems with Applications"},{"key":"2024030113560794200_bib60","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1080\/07408179308964266","article-title":"Linear programming, simulated annealing and tabu search heuristics for lotsizing in bottleneck assembly systems","volume":"25","author":"Kuik","year":"1993","journal-title":"IIE Transactions"},{"key":"2024030113560794200_bib61","doi-asserted-by":"crossref","first-page":"252","DOI":"10.1016\/j.future.2017.10.052","article-title":"Socio evolution & learning optimization algorithm: A socio-inspired optimization methodology","volume":"81","author":"Kumar","year":"2018","journal-title":"Future Generation Computer Systems"},{"key":"2024030113560794200_bib63","doi-asserted-by":"crossref","first-page":"1269","DOI":"10.1007\/s00366-018-0662-y","article-title":"Modified symbiotic organisms search for structural optimization","volume":"35","author":"Kumar","year":"2019","journal-title":"Engineering with Computers"},{"key":"2024030113560794200_bib64","doi-asserted-by":"crossref","first-page":"1217","DOI":"10.1007\/s42107-020-00271-x","article-title":"Improved metaheuristics through migration-based search and an acceptance probability for truss optimization","volume":"21","author":"Kumar","year":"2020","journal-title":"Asian Journal of Civil Engineering"},{"key":"2024030113560794200_bib65","doi-asserted-by":"crossref","first-page":"84982","DOI":"10.1109\/ACCESS.2021.3087739","article-title":"Mopgo: A new physics-based multi-objective plasma generation optimizer for solving structural optimization problems","volume":"9","author":"Kumar","year":"2021","journal-title":"IEEE Access"},{"key":"2024030113560794200_bib62","doi-asserted-by":"crossref","first-page":"5866","DOI":"10.3390\/en14185866","article-title":"Off-grid rural electrification in india using renewable energy resources and different battery technologies with a dynamic differential annealed optimization","volume":"14","author":"Kumar","year":"2021","journal-title":"Energies"},{"key":"2024030113560794200_bib66","doi-asserted-by":"crossref","first-page":"3439","DOI":"10.1007\/s00366-020-01010-1","article-title":"Multi-objective modified heat transfer search for truss optimization","volume":"37","author":"Kumar","year":"2021","journal-title":"Engineering with Computers"},{"key":"2024030113560794200_bib67","doi-asserted-by":"crossref","first-page":"114511","DOI":"10.1016\/j.eswa.2020.114511","article-title":"Multi-objective passing vehicle search algorithm for structure optimization","volume":"169","author":"Kumar","year":"2021","journal-title":"Expert Systems with Applications"},{"key":"2024030113560794200_bib69","doi-asserted-by":"crossref","first-page":"106556","DOI":"10.1016\/j.knosys.2020.106556","article-title":"Hybrid heat transfer search and passing vehicle search optimizer for multi-objective structural optimization","volume":"212","author":"Kumar","year":"2021","journal-title":"Knowledge-Based Systems"},{"key":"2024030113560794200_bib68","doi-asserted-by":"crossref","first-page":"106811","DOI":"10.1016\/j.knosys.2021.106811","article-title":"Multiobjecitve structural optimization using improved heat transfer search","volume":"219","author":"Kumar","year":"2021","journal-title":"Knowledge-Based Systems"},{"key":"2024030113560794200_bib72","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1080\/23080477.2021.1975074","article-title":"Multi-objective teaching-learning-based optimization for structure optimization","volume":"10","author":"Kumar","year":"2022","journal-title":"Smart Science"},{"key":"2024030113560794200_bib71","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s00500-022-06930-2","article-title":"Performance enhancement of meta-heuristics through random mutation and simulated annealing-based selection for concurrent topology and sizing optimization of truss structures","volume":"26","author":"Kumar","year":"2022","journal-title":"Soft Computing"},{"key":"2024030113560794200_bib70","doi-asserted-by":"crossref","first-page":"108422","DOI":"10.1016\/j.knosys.2022.108422","article-title":"Moteo: A novel physics-based multiobjective thermal exchange optimization algorithm to design truss structures","volume":"242","author":"Kumar","year":"2022","journal-title":"Knowledge-Based Systems"},{"key":"2024030113560794200_bib73","doi-asserted-by":"crossref","first-page":"110192","DOI":"10.1016\/j.knosys.2022.110192","article-title":"Chaotic marine predators algorithm for global optimization of real-world engineering problems","volume":"261","author":"Kumar","year":"2023","journal-title":"Knowledge-Based Systems"},{"key":"2024030113560794200_bib74","doi-asserted-by":"crossref","first-page":"717","DOI":"10.1007\/s11831-021-09586-7","article-title":"Comparative performance of twelve metaheuristics for wind farm layout optimisation","volume":"29","author":"Kunakote","year":"2022","journal-title":"Archives of Computational Methods in Engineering"},{"key":"2024030113560794200_bib75","doi-asserted-by":"crossref","first-page":"678","DOI":"10.1057\/jors.1996.79","article-title":"Search heuristics for resource constrained project scheduling","volume":"47","author":"Lee","year":"1996","journal-title":"Journal of the Operational Research Society"},{"key":"2024030113560794200_bib76","doi-asserted-by":"crossref","first-page":"300","DOI":"10.1016\/j.future.2020.03.055","article-title":"Slime mould algorithm: A new method for stochastic optimization","volume":"111","author":"Li","year":"2020","journal-title":"Future Generation Computer Systems"},{"key":"2024030113560794200_bib77","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.swevo.2017.09.010","article-title":"Opposition based learning: A literature review","volume":"39","author":"Mahdavi","year":"2018","journal-title":"Swarm and Evolutionary Computation"},{"key":"2024030113560794200_bib78","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s00521-021-06758-1","article-title":"Dynamic differential annealing-based anti-spoofing model for fingerprint detection using cnn","volume":"34","author":"Maheswari","year":"2022","journal-title":"Neural Computing and Applications"},{"key":"2024030113560794200_bib79","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1515\/mt-2022-0259","article-title":"A novel generalized normal distribution optimizer with elite oppositional based learning for optimization of mechanical engineering problems","volume":"65","author":"Mehta","year":"2023","journal-title":"Materials Testing"},{"key":"2024030113560794200_bib80","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.advengsoft.2013.12.007","article-title":"Grey wolf optimizer","volume":"69","author":"Mirjalili","year":"2014","journal-title":"Advances in Engineering Software"},{"key":"2024030113560794200_bib81","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1016\/j.advengsoft.2017.07.002","article-title":"Salp swarm algorithm: A bio-inspired optimizer for engineering design problems","volume":"114","author":"Mirjalili","year":"2017","journal-title":"Advances in Engineering Software"},{"key":"2024030113560794200_bib82","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/CEC48606.2020.9185901","article-title":"Evaluating the performance of adaptive gainingsharing knowledge based algorithm on cec 2020 benchmark problems","volume-title":"2020 IEEE Congress on Evolutionary Computation (CEC)","author":"Mohamed","year":"2020"},{"key":"2024030113560794200_bib83","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1016\/j.engappai.2019.08.025","article-title":"Poor and rich optimization algorithm: A new human-based and multi populations algorithm","volume":"86","author":"Moosavi","year":"2019","journal-title":"Engineering Applications of Artificial Intelligence"},{"key":"2024030113560794200_bib84","doi-asserted-by":"crossref","first-page":"113364","DOI":"10.1016\/j.eswa.2020.113364","article-title":"An efficient henry gas solubility optimization for feature selection","volume":"152","author":"Neggaz","year":"2020","journal-title":"Expert Systems with Applications"},{"key":"2024030113560794200_bib85","doi-asserted-by":"crossref","first-page":"2235","DOI":"10.1093\/jcde\/qwac095","article-title":"Addressing constrained engineering problems and feature selection with a time-based leadership salp-based algorithm with competitive learning","volume":"9","author":"Qaraad","year":"2022","journal-title":"Journal of Computational Design and Engineering"},{"key":"2024030113560794200_bib86","first-page":"1","article-title":"Improved multi-operator differential evolution algorithm for solving unconstrained problems","volume-title":"2020 IEEE Congress on Evolutionary Computation (CEC)","author":"Sallam","year":"2020"},{"key":"2024030113560794200_bib87","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1016\/j.advengsoft.2017.01.004","article-title":"Grasshopper optimisation algorithm: theory and application","volume":"105","author":"Saremi","year":"2017","journal-title":"Advances in Engineering Software"},{"key":"2024030113560794200_bib88","first-page":"1","article-title":"A comprehensive survey on aquila optimizer","author":"Sasmal","year":"2023","journal-title":"Archives of Computational Methods in Engineering"},{"key":"2024030113560794200_bib89","first-page":"1","article-title":"Reptile search algorithm: Theory, variants, applications, and performance evaluation","author":"Sasmal","year":"2023","journal-title":"Archives of Computational Methods in Engineering"},{"key":"2024030113560794200_bib90","article-title":"Very deep convolutional networks for large-scale image recognition","author":"Simonyan","year":"2014"},{"key":"2024030113560794200_bib91","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1111\/itor.12001","article-title":"Metaheuristics\u2019the metaphor exposed","volume":"22","author":"S\u00f6rensen","year":"2015","journal-title":"International Transactions in Operational Research"},{"key":"2024030113560794200_bib92","doi-asserted-by":"crossref","first-page":"641","DOI":"10.1007\/s00366-019-00846-6","article-title":"Multi-objective heat transfer search algorithm for truss optimization","volume":"37","author":"Tejani","year":"2021","journal-title":"Engineering with Computers"},{"key":"2024030113560794200_bib93","first-page":"695","article-title":"Opposition-based learning: a new scheme for machine intelligence","volume-title":"International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce (CIMCA-IAWTIC\u201906)","author":"Tizhoosh","year":"2005"},{"key":"2024030113560794200_bib94","first-page":"1","article-title":"Memory-based harris hawk optimization with learning agents: a feature selection approach","volume":"38","author":"Too","year":"2021","journal-title":"Engineering with Computers"},{"key":"2024030113560794200_bib95","doi-asserted-by":"crossref","first-page":"473","DOI":"10.1109\/TEVC.2018.2869405","article-title":"Variable-length particle swarm optimization for feature selection on high-dimensional classification","volume":"23","author":"Tran","year":"2018","journal-title":"IEEE Transactions on Evolutionary Computation"},{"key":"2024030113560794200_bib96","doi-asserted-by":"crossref","first-page":"116468","DOI":"10.1016\/j.eswa.2021.116468","article-title":"A new optimization algorithm inspired by the quest for the evolution of human society: Human felicity algorithm","volume":"193","author":"Veysari","year":"2022","journal-title":"Expert Systems with Applications"},{"key":"2024030113560794200_bib97","doi-asserted-by":"crossref","first-page":"4750","DOI":"10.1109\/CEC.2007.4425095","article-title":"Opposition-based particle swarm algorithm with cauchy mutation","volume-title":"2007 IEEE Congress on Evolutionary Computation","author":"Wang","year":"2007"},{"key":"2024030113560794200_bib98","doi-asserted-by":"crossref","first-page":"qwad062","DOI":"10.1093\/jcde\/qwad062","article-title":"A modified smell agent optimization for global optimization and industrial engineering design problems","volume":"10","author":"Wang","year":"2023","journal-title":"Journal of Computational Design and Engineering"},{"key":"2024030113560794200_bib99","first-page":"385","article-title":"Ensemble of four metaheuristic using a weighted sum technique for aircraft wing design","volume":"48","author":"Wansasueb","year":"2021","journal-title":"Engineering and Applied Science Research"},{"key":"2024030113560794200_bib100","doi-asserted-by":"crossref","first-page":"196","DOI":"10.1007\/978-1-4612-4380-9_16","article-title":"Individual comparisons by ranking methods","volume-title":"Breakthroughs in Statistics","author":"Wilcoxon","year":"1992"},{"key":"2024030113560794200_bib101","doi-asserted-by":"crossref","first-page":"1311","DOI":"10.3390\/met11081311","article-title":"Ground structures-based topology optimization of a morphing wing using a metaheuristic algorithm","volume":"11","author":"Winyangkul","year":"2021","journal-title":"Metals"},{"key":"2024030113560794200_bib102","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1109\/4235.585893","article-title":"No free lunch theorems for optimization","volume":"1","author":"Wolpert","year":"1997","journal-title":"IEEE Transactions on Evolutionary Computation"},{"key":"2024030113560794200_bib103","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3340848","article-title":"Self-adaptive particle swarm optimization for large-scale feature selection in classification","volume":"13","author":"Xue","year":"2019","journal-title":"ACM Transactions on Knowledge Discovery from Data (TKDD)"},{"key":"2024030113560794200_bib104","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1504\/IJBIC.2011.039907","article-title":"Review of meta-heuristics and generalised evolutionary walk algorithm","volume":"3","author":"Yang","year":"2011","journal-title":"International Journal of Bio-Inspired Computation"},{"key":"2024030113560794200_bib105","doi-asserted-by":"crossref","first-page":"e12992","DOI":"10.1111\/exsy.12992","article-title":"A new chaotic l\u00e9vy flight distribution optimization algorithm for solving constrained engineering problems","volume":"39","author":"Y\u0131ld\u0131z","year":"2022","journal-title":"Expert Systems"},{"key":"2024030113560794200_bib106","doi-asserted-by":"crossref","first-page":"110554","DOI":"10.1016\/j.knosys.2023.110554","article-title":"A novel hybrid arithmetic optimization algorithm for solving constrained optimization problems","volume":"271","author":"Y\u0131ld\u0131z","year":"2023","journal-title":"Knowledge-Based Systems"},{"key":"2024030113560794200_bib107","doi-asserted-by":"crossref","first-page":"14173","DOI":"10.3934\/mbe.2022660","article-title":"Enhanced aquila optimizer algorithm for global optimization and constrained engineering problems","volume":"19","author":"Yu","year":"2022","journal-title":"Mathematical Biosciences and Engineering"},{"key":"2024030113560794200_bib109","doi-asserted-by":"crossref","first-page":"3741","DOI":"10.1007\/s00366-020-01028-5","article-title":"Boosted binary harris hawks optimizer and feature selection","volume":"37","author":"Zhang","year":"2021","journal-title":"Engineering with Computers"},{"key":"2024030113560794200_bib108","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/j.neucom.2020.10.038","article-title":"Towards augmented kernel extreme learning models for bankruptcy prediction: algorithmic behavior and comprehensive analysis","volume":"430","author":"Zhang","year":"2021","journal-title":"Neurocomputing"},{"key":"2024030113560794200_bib110","doi-asserted-by":"crossref","first-page":"1007","DOI":"10.1093\/jcde\/qwac038","article-title":"Opposition-based ant colony optimization with all-dimension neighborhood search for engineering design","volume":"9","author":"Zhao","year":"2022","journal-title":"Journal of Computational Design and Engineering"},{"key":"2024030113560794200_bib111","doi-asserted-by":"crossref","first-page":"329","DOI":"10.1093\/jcde\/qwac135","article-title":"A multi-strategy enhanced african vultures optimization algorithm for global optimization problems","volume":"10","author":"Zheng","year":"2023","journal-title":"Journal of Computational Design and Engineering"}],"container-title":["Journal of Computational Design and Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/jcde\/advance-article-pdf\/doi\/10.1093\/jcde\/qwad108\/56210117\/qwad108.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/jcde\/article-pdf\/11\/1\/49\/56812100\/qwad108.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/jcde\/article-pdf\/11\/1\/49\/56812100\/qwad108.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,1]],"date-time":"2024-03-01T13:59:46Z","timestamp":1709301586000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/jcde\/article\/11\/1\/49\/7571569"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,28]]},"references-count":111,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2023,12,28]]}},"URL":"https:\/\/doi.org\/10.1093\/jcde\/qwad108","relation":{},"ISSN":["2288-5048"],"issn-type":[{"value":"2288-5048","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2024,2]]},"published":{"date-parts":[[2023,12,28]]}}}