{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,30]],"date-time":"2026-01-30T07:25:41Z","timestamp":1769757941143,"version":"3.49.0"},"reference-count":93,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2025,2,1]],"date-time":"2025-02-01T00:00:00Z","timestamp":1738368000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Jilin Provincial Department of Science and Technology","award":["YDZJ202201ZYTS565"],"award-info":[{"award-number":["YDZJ202201ZYTS565"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>This paper introduces a bio-inspired meta-heuristic algorithm, the Besiege and Conquer Algorithm (BCA), developed to tackle complex and high-dimensional optimization problems. Drawing inspiration from the concept of symmetry and guerrilla warfare strategies, the BCA incorporates four core components: besiege, conquer, balance, and feedback. The besiege strategy strengthens exploration, while the conquer strategy enhances exploitation. Balance and feedback mechanisms maintain a dynamic equilibrium between these capabilities, ensuring robust optimization performance. The algorithm\u2019s effectiveness is validated through benchmark test functions, demonstrating superior results in comparison with existing methods, supported by Friedman rankings and Wilcoxon signed-rank tests. Beyond theoretical and experimental validation, the BCA showcases its real-world relevance through applications in engineering design and classification problems, addressing practical challenges. These results underline the algorithm\u2019s strong exploration, exploitation, and convergence capabilities and its potential to contribute meaningfully to diverse real-world domains.<\/jats:p>","DOI":"10.3390\/sym17020217","type":"journal-article","created":{"date-parts":[[2025,2,3]],"date-time":"2025-02-03T05:36:32Z","timestamp":1738560992000},"page":"217","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["BCA: Besiege and Conquer Algorithm"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9149-2922","authenticated-orcid":false,"given":"Jianhua","family":"Jiang","sequence":"first","affiliation":[{"name":"Center for Artificial Intelligence, Jilin University of Finance and Economics, Changchun 130117, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6099-4877","authenticated-orcid":false,"given":"Xianqiu","family":"Meng","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Jilin University, Changchun 130012, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-9233-9851","authenticated-orcid":false,"given":"Jiaqi","family":"Wu","sequence":"additional","affiliation":[{"name":"Center for Artificial Intelligence, Jilin University of Finance and Economics, Changchun 130117, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jun","family":"Tian","sequence":"additional","affiliation":[{"name":"Center for Artificial Intelligence, Jilin University of Finance and Economics, Changchun 130117, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4450-7941","authenticated-orcid":false,"given":"Gaochao","family":"Xu","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Jilin University, Changchun 130012, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9215-4979","authenticated-orcid":false,"given":"Weihua","family":"Li","sequence":"additional","affiliation":[{"name":"School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Auckland 1010, New Zealand"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,2,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"121674","DOI":"10.1016\/j.ins.2024.121674","article-title":"Optimizing energy efficiency in unrelated parallel machine scheduling problem through reinforcement learning","volume":"693","author":"Bernal","year":"2024","journal-title":"Inf. Sci."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1109\/61.368411","article-title":"Neural network system using the multi-layer perceptron technique for the recognition of pd pulse shapes due to cavities and electrical trees","volume":"10","author":"Mazroua","year":"1995","journal-title":"IEEE Trans. Power Deliv."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1371","DOI":"10.1109\/TBCAS.2023.3299084","article-title":"Automlp: A framework for the acceleration of multi-layer perceptron models on FPGAs for real-time atrial fibrillation disease detection","volume":"12","author":"Chen","year":"2023","journal-title":"IEEE Trans. Biomed. Circuits Syst."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"111192","DOI":"10.1016\/j.asoc.2023.111192","article-title":"A genetic operators-based ant lion optimiser for training a medical multi-layer perceptron","volume":"151","author":"Rojas","year":"2024","journal-title":"Appl. Soft Comput."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"325","DOI":"10.1109\/TNN.2004.841777","article-title":"Linear-least-squares initialization of multilayer perceptrons through backpropagation of the desired response","volume":"16","author":"Erdogmus","year":"2005","journal-title":"IEEE Trans. Neural Netw."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s00366-021-01554-w","article-title":"A global optimizer inspired from the survival strategies of flying foxes","volume":"39","author":"Zervoudakis","year":"2023","journal-title":"Eng. Comput."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Po\u0142ap, D., and Wo\u017aniak, M. (2017). Polar bear optimization algorithm: Meta-heuristic with fast population movement and dynamic birth and death mechanism. Symmetry, 9.","DOI":"10.3390\/sym9100203"},{"key":"ref_8","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":"Adv. Eng. Softw."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1109\/MCI.2006.329691","article-title":"Ant colony optimization","volume":"1","author":"Dorigo","year":"2006","journal-title":"IEEE Comput. Intell. Mag."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1038\/scientificamerican0792-66","article-title":"Genetic algorithms","volume":"267","author":"Holland","year":"1992","journal-title":"Sci. Am."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"109838","DOI":"10.1016\/j.compeleceng.2024.109838","article-title":"An optimized multilayer perceptron-based network intrusion detection using gray wolf optimization","volume":"120","author":"Ali","year":"2024","journal-title":"Comput. Electr. Eng."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"108766","DOI":"10.1016\/j.asoc.2022.108766","article-title":"Multi-layer perceptron classification method of medical data based on biogeography-based optimization algorithm with probability distributions","volume":"121","author":"Li","year":"2022","journal-title":"Appl. Soft Comput."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"106559","DOI":"10.1016\/j.cie.2020.106559","article-title":"A mayfly optimization algorithm","volume":"145","author":"Zervoudakis","year":"2020","journal-title":"Comput. Ind. Eng."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"129018","DOI":"10.1016\/j.neucom.2024.129018","article-title":"An adaptation of hybrid binary optimization algorithms for medical image feature selection in neural network for classification of breast cancer","volume":"617","author":"Oyelade","year":"2024","journal-title":"Neurocomputing"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"101760","DOI":"10.1016\/j.swevo.2024.101760","article-title":"A novel importance-guided particle swarm optimization based on mlp for solving large-scale feature selection problems","volume":"91","author":"Xue","year":"2024","journal-title":"Swarm Evol. Comput."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"101783","DOI":"10.1016\/j.swevo.2024.101783","article-title":"A multi-strategy self-adaptive differential evolution algorithm for assembly hybrid flowshop lot-streaming scheduling with component sharing","volume":"92","author":"Lu","year":"2025","journal-title":"Swarm Evol. Comput."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1111\/itor.12001","article-title":"Metaheuristics\u2014The metaphor exposed","volume":"22","year":"2015","journal-title":"Int. Trans. Oper. Res."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"125446","DOI":"10.1016\/j.eswa.2024.125446","article-title":"A hybrid artificial bee colony algorithm with high robustness for the multiple traveling salesman problem with multiple depots","volume":"260","author":"Tong","year":"2025","journal-title":"Expert Syst. Appl."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"125133","DOI":"10.1016\/j.eswa.2024.125133","article-title":"Enhancing corporate bankruptcy prediction via a hybrid genetic algorithm and domain adaptation learning architecture","volume":"258","author":"Nortey","year":"2024","journal-title":"Expert Syst. Appl."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"110549","DOI":"10.1016\/j.knosys.2023.110549","article-title":"Multilayer perceptron neural network with regression and ranking loss for patient-specific quality assurance","volume":"271","author":"Liu","year":"2023","journal-title":"Knowl.-Based Syst."},{"key":"ref_21","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 Syst. Appl."},{"key":"ref_22","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 Syst. Appl."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Diep, Q.B. (2019, January 10\u201313). Self-organizing migrating algorithm team to team adaptive\u2013SOMA T3A. Proceedings of the 2019 IEEE Congress on Evolutionary Computation (CEC), Wellington, New Zealand.","DOI":"10.1109\/CEC.2019.8790202"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"715","DOI":"10.1007\/s00500-018-3102-4","article-title":"Butterfly optimization algorithm: A novel approach for global optimization","volume":"23","author":"Arora","year":"2019","journal-title":"Soft Comput."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1023\/A:1008202821328","article-title":"Differential evolution\u2013a simple and efficient heuristic for global optimization over continuous spaces","volume":"11","author":"Storn","year":"1997","journal-title":"J. Glob. Optim."},{"key":"ref_26","unstructured":"Kennedy, J., and Eberhart, R. (December, January 27). Particle swarm optimization. Proceedings of the ICNN\u201995-International Conference on Neural Networks, Perth, WA, Australia."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1583","DOI":"10.1002\/nme.1620210904","article-title":"A study of mathematical programming methods for structural optimization","volume":"21","author":"Belegundu","year":"1985","journal-title":"Part I Theory Int. J. Numer. Methods Eng."},{"key":"ref_28","first-page":"83","article-title":"Practical approach to optimum gear train design","volume":"20","author":"Prayoonrat","year":"1988","journal-title":"Comput. Des."},{"key":"ref_29","unstructured":"McGarry, K.J., Wermter, S., and MacIntyre, J. (1999, January 10\u201316). Knowledge extraction from radial basis function networks and multilayer perceptrons. Proceedings of the IJCNN\u201999. International Joint Conference on Neural Networks. Proceedings (Cat. No. 99CH36339), Washington, DC, USA."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"416","DOI":"10.1037\/0278-7393.17.3.416","article-title":"Influence of prior knowledge on concept acquisition: Experimental and computational results","volume":"17","author":"Pazzani","year":"1991","journal-title":"J. Exp. Psychol. Learn. Mem. Cogn."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Aha, D.W. (1991). Incremental constructive induction: An instance-based approach. Machine Learning Proceedings 1991, Morgan Kaufmann.","DOI":"10.1016\/B978-1-55860-200-7.50027-1"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"115197","DOI":"10.1016\/j.eswa.2021.115197","article-title":"Meta-heuristic algorithms to truss optimization: Literature mapping and application","volume":"182","author":"Renkavieski","year":"2021","journal-title":"Expert Syst. Appl."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/j.ins.2021.06.062","article-title":"Affine invariance of meta-heuristic algorithms","volume":"576","author":"Jian","year":"2021","journal-title":"Inf. Sci."},{"key":"ref_34","unstructured":"Rechenberg, I. (1973). Evolution Strategy: Optimization of Technical Systems by Means of Biological Evolution, Fromman-Holzboog."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"228","DOI":"10.1016\/0167-2789(90)90076-2","article-title":"Co-evolving parasites improve simulated evolution as an optimization procedure","volume":"42","author":"Hillis","year":"1990","journal-title":"Phys. D Nonlinear Phenom."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Atashpaz-Gargari, E., and Lucas, C. (2007, January 25\u201328). Imperialist competitive algorithm: An algorithm for optimization inspired by imperialis-tic competition. Proceedings of the 2007 IEEE Congress on Evolutionary Computation, Singapore.","DOI":"10.1109\/CEC.2007.4425083"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1016\/j.cageo.2011.12.011","article-title":"Transforming geocentric cartesian coordinates to geodetic coordinates by using differential search algorithm","volume":"46","author":"Civicioglu","year":"2012","journal-title":"Comput. Geosci."},{"key":"ref_38","first-page":"8121","article-title":"Backtracking search optimization algorithm for numerical optimization problems","volume":"219","author":"Civicioglu","year":"2013","journal-title":"Appl. Math. Comput."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.knosys.2014.07.025","article-title":"Stochastic fractal search: A powerful meta-heuristic algorithm","volume":"75","author":"Salimi","year":"2015","journal-title":"Knowl.-Based Syst."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"815","DOI":"10.1631\/FITEE.1601553","article-title":"Synergistic fibroblast optimization: A novel nature-inspired computing algorithm","volume":"19","author":"Dhivyaprabha","year":"2018","journal-title":"Front. Inf. Technol. Electron. Eng."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1959017","DOI":"10.1142\/S0218001419590171","article-title":"Who: A new evolutionary algorithm bio-inspired by wildebeests with a case study on bank customer segmentation","volume":"33","author":"Motevali","year":"2019","journal-title":"Int. J. Pattern Recognit. Artif. Intell."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1016\/j.eij.2020.08.003","article-title":"A new evolutionary algorithm: Learner performance based behavior algorithm","volume":"22","author":"Rahman","year":"2021","journal-title":"Egypt. Inform. J."},{"key":"ref_43","first-page":"303","article-title":"Teaching\u2013learning-based optimization: A novel method for constrained mechanical design optimization problems","volume":"43","author":"Rao","year":"2011","journal-title":"Comput. Des."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"973","DOI":"10.1109\/TEVC.2009.2011992","article-title":"Group search optimizer: An optimization algorithm inspired by animal searching behavior","volume":"13","author":"He","year":"2009","journal-title":"IEEE Trans. Evol. Comput."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.compstruc.2014.04.005","article-title":"Colliding bodies optimization: A novel meta-heuristic method","volume":"139","author":"Kaveh","year":"2014","journal-title":"Comput. Struct."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1016\/j.asoc.2013.12.005","article-title":"League championship algorithm (LCA): An algorithm for global optimization inspired by sport champi-onships","volume":"16","author":"Kashan","year":"2014","journal-title":"Appl. Soft Comput."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"464","DOI":"10.1016\/j.apm.2018.06.036","article-title":"Queuing search algorithm: A novel metaheuristic algorithm for solving engineering optimization problems","volume":"63","author":"Zhang","year":"2018","journal-title":"Appl. Math. Model."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"318","DOI":"10.1109\/ICICISYS.2009.5357838","article-title":"Human-inspired algorithms for continuous function optimization","volume":"Volume 1","author":"Zhang","year":"2009","journal-title":"Proceedings of the 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"199","DOI":"10.5923\/j.eee.20120204.05","article-title":"Anarchic society optimization based pid control of an automatic voltage regulator (avr) system","volume":"2","author":"Shayeghi","year":"2012","journal-title":"Electr. Electron. Eng."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"850","DOI":"10.1007\/s10489-017-0903-6","article-title":"Human mental search: A new population-based meta-heuristic optimization algorithm","volume":"47","author":"Mousavirad","year":"2017","journal-title":"Appl. Intell."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1016\/j.asoc.2017.11.043","article-title":"Volleyball premier league algorithm","volume":"64","author":"Moghdani","year":"2018","journal-title":"Appl. Soft Comput."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"1501","DOI":"10.1007\/s13042-019-01053-x","article-title":"Gaining-sharing knowledge based algorithm for solving optimization problems: A novel nature-inspired algorithm","volume":"11","author":"Mohamed","year":"2020","journal-title":"Int. J. Mach. Learn. Cybern."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"5011","DOI":"10.1007\/s00521-020-05296-6","article-title":"Coronavirus herd immunity optimizer (CHIO)","volume":"33","author":"Alyasseri","year":"2021","journal-title":"Neural Comput. Appl."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"409","DOI":"10.1007\/s00521-021-06392-x","article-title":"A novel meta-heuristic algorithm for solving numerical optimization problems: Ali baba and the forty thieves","volume":"34","author":"Braik","year":"2022","journal-title":"Neural Comput. Appl."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"671","DOI":"10.1126\/science.220.4598.671","article-title":"Optimization by simulated annealing","volume":"220","author":"Kirkpatrick","year":"1983","journal-title":"Science"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1016\/j.swevo.2018.02.018","article-title":"A comprehensive survey on gravitational search algorithm","volume":"41","author":"Rashedi","year":"2018","journal-title":"Swarm Evol. Comput."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"425","DOI":"10.2528\/PIER07082403","article-title":"Central force optimization","volume":"77","author":"Formato","year":"2007","journal-title":"Prog Electromagn Res."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"1097","DOI":"10.1016\/S0305-0548(97)00031-2","article-title":"Variable neighborhood search","volume":"24","author":"Hansen","year":"1997","journal-title":"Comput. Oper. Res."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1016\/j.advengsoft.2005.04.005","article-title":"A new optimization method: Big bang\u2013big crunch","volume":"37","author":"Erol","year":"2006","journal-title":"Adv. Eng. Softw."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"2232","DOI":"10.1016\/j.ins.2009.03.004","article-title":"GSA: A gravitational search algorithm","volume":"179","author":"Rashedi","year":"2009","journal-title":"Inf. Sci."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1016\/j.ins.2012.08.023","article-title":"Black hole: A new heuristic optimization approach for data clustering","volume":"222","author":"Hatamlou","year":"2013","journal-title":"Inf. Sci."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"315","DOI":"10.1016\/j.asoc.2015.07.028","article-title":"Lightning search algorithm","volume":"36","author":"Shareef","year":"2015","journal-title":"Appl. Soft Comput."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"495","DOI":"10.1007\/s00521-015-1870-7","article-title":"Multi-verse optimizer: A nature-inspired algorithm for global optimization","volume":"27","author":"Mirjalili","year":"2016","journal-title":"Neural Comput. Appl."},{"key":"ref_64","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":"Adv. Eng. Softw."},{"key":"ref_65","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":"Knowl.-Based Syst."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"106314","DOI":"10.1016\/j.asoc.2020.106314","article-title":"Enhancing tree-seed algorithm via feed-back mechanism for optimizing continuous problems","volume":"92","author":"Jiang","year":"2020","journal-title":"Appl. Soft Comput."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.swevo.2016.12.005","article-title":"A survey of swarm intelligence for dynamic optimization: Algorithms and applications","volume":"33","author":"Mavrovouniotis","year":"2017","journal-title":"Swarm Evol. Comput."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"104303","DOI":"10.1016\/j.engappai.2021.104303","article-title":"TriTSA: Triple tree-seed algorithm for dimensional continuous optimization and constrained engineering problems","volume":"104","author":"Jiang","year":"2021","journal-title":"Eng. Appl. Artif. Intell."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"118311","DOI":"10.1016\/j.eswa.2022.118311","article-title":"Enhance tree-seed algorithm using hierarchy mechanism for constrained optimization problems","volume":"209","author":"Jiang","year":"2022","journal-title":"Expert Syst. Appl."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"109100","DOI":"10.1016\/j.knosys.2022.109100","article-title":"DSGWO: An improved grey wolf optimizer with diversity enhanced strategy based on group-stage competition and balance mechanisms","volume":"250","author":"Jiang","year":"2022","journal-title":"Knowl.-Based Syst."},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Yang, X.-S. (2009). Firefly algorithms for multimodal optimization. International Symposium on Stochastic Algorithms, Springer.","DOI":"10.1007\/978-3-642-04944-6_14"},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/j.knosys.2011.07.001","article-title":"A new fruit fly optimization algorithm: Taking the financial distress model as an example","volume":"26","author":"Pan","year":"2012","journal-title":"Knowl.-Based Syst."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.advengsoft.2015.01.010","article-title":"The ant lion optimizer","volume":"83","author":"Mirjalili","year":"2015","journal-title":"Adv. Eng. Softw."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"6686","DOI":"10.1016\/j.eswa.2015.04.055","article-title":"TSA: Tree-seed algorithm for continuous optimization","volume":"42","author":"Kiran","year":"2015","journal-title":"Expert Syst. Appl."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"1053","DOI":"10.1007\/s00521-015-1920-1","article-title":"Dragonfly algorithm: A new meta-heuristic optimization technique for solving single-objective, discrete, and multi-objective problems","volume":"27","author":"Mirjalili","year":"2016","journal-title":"Neural Comput. Appl."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1016\/j.advengsoft.2016.01.008","article-title":"The whale optimization algorithm","volume":"95","author":"Mirjalili","year":"2016","journal-title":"Adv. Eng. Softw."},{"key":"ref_77","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":"Adv. Eng. Softw."},{"key":"ref_78","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":"Adv. Eng. Softw."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"2237","DOI":"10.1007\/s10462-019-09732-5","article-title":"Novel meta-heuristic bald eagle search optimisation algorithm","volume":"53","author":"Alsattar","year":"2020","journal-title":"Artif. Intell. Rev."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"107250","DOI":"10.1016\/j.cie.2021.107250","article-title":"Aquila optimizer: A novel meta-heuristic optimization algorithm","volume":"157","author":"Abualigah","year":"2021","journal-title":"Comput. Ind. Eng."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"114107","DOI":"10.1016\/j.eswa.2020.114107","article-title":"Red fox optimization algorithm","volume":"166","year":"2021","journal-title":"Expert Syst. Appl."},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"2571863","DOI":"10.1155\/2021\/2571863","article-title":"Dingo Optimizer: A nature-inspired metaheuristic approach for engineering problems","volume":"2021","author":"Bairwa","year":"2021","journal-title":"Math. Probl. Eng."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"114685","DOI":"10.1016\/j.eswa.2021.114685","article-title":"Chameleon swarm algorithm: A bio-inspired optimizer for solving engineering design problems","volume":"174","author":"Braik","year":"2021","journal-title":"Expert. Syst. Appl."},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"108457","DOI":"10.1016\/j.knosys.2022.108457","article-title":"White shark optimizer: A novel bio-inspired meta-heuristic algorithm for global optimization problems","volume":"243","author":"Braik","year":"2022","journal-title":"Knowl.-Based Syst."},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"17298806241301581","DOI":"10.1177\/17298806241301581","article-title":"Multi-layer perceptron-particle swarm optimization: A lightweight optimization algorithm for the model predictive control local planner","volume":"21","author":"Guan","year":"2024","journal-title":"Int. J. Adv. Robot. Syst."},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"150","DOI":"10.11648\/j.com.20150305.21","article-title":"Optimization of multi-layer perceptron neural network using genetic algorithm for arrhythmia classification","volume":"3","author":"Kumari","year":"2015","journal-title":"Communications"},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"382","DOI":"10.1016\/j.asoc.2014.03.039","article-title":"Differential evolution algorithms applied to neural network training suffer from stagnation","volume":"21","author":"Piotrowski","year":"2014","journal-title":"Appl. Soft Comput."},{"key":"ref_88","first-page":"1","article-title":"The hunger games: Weaponizing food","volume":"37","author":"Stober","year":"2022","journal-title":"Mark. Ideas"},{"key":"ref_89","first-page":"1846","article-title":"Characteristics of the hero in contemporary arabic poetry","volume":"18","author":"Madhi","year":"2021","journal-title":"PalArch\u2019s J. Archaeol. Egypt\/Egyptology"},{"key":"ref_90","unstructured":"Janson, H.W. (2021). The equestrian monument from cangrande della scala to peter the great. Aspects of the Renaissance, University of Texas Press."},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1108\/eb024706","article-title":"The pareto principle: Its use and abuse","volume":"1","author":"Sanders","year":"1987","journal-title":"J. Serv. Mark."},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"327","DOI":"10.1016\/j.neucom.2019.08.095","article-title":"Hybrid neural networks for big data classification","volume":"390","author":"Zamora","year":"2020","journal-title":"Neurocomputing"},{"key":"ref_93","doi-asserted-by":"crossref","first-page":"114676","DOI":"10.1016\/j.eswa.2021.114676","article-title":"AGWO: Advanced GWO in multi-layer perception optimization","volume":"173","author":"Meng","year":"2021","journal-title":"Expert Syst. Appl."}],"container-title":["Symmetry"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2073-8994\/17\/2\/217\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T16:25:18Z","timestamp":1760027118000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2073-8994\/17\/2\/217"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,2,1]]},"references-count":93,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2025,2]]}},"alternative-id":["sym17020217"],"URL":"https:\/\/doi.org\/10.3390\/sym17020217","relation":{},"ISSN":["2073-8994"],"issn-type":[{"value":"2073-8994","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,2,1]]}}}