{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T04:17:09Z","timestamp":1784693829275,"version":"3.55.0"},"reference-count":101,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2024,9,21]],"date-time":"2024-09-21T00:00:00Z","timestamp":1726876800000},"content-version":"vor","delay-in-days":21,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,8,31]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Metaheuristic algorithms are increasingly utilized to solve complex optimization problems because they can efficiently explore large solution spaces. The moss growth optimization (MGO), introduced in this paper, is an algorithm inspired by the moss growth in the natural environment. The MGO algorithm initially determines the evolutionary direction of the population through a mechanism called the determination of wind direction, which employs a method of partitioning the population. Meanwhile, drawing inspiration from the asexual reproduction, sexual reproduction, and vegetative reproduction of moss, two novel search strategies, namely spore dispersal search and dual propagation search, are proposed for exploration and exploitation, respectively. Finally, the cryptobiosis mechanism alters the traditional metaheuristic algorithm\u2019s approach of directly modifying individuals\u2019 solutions, preventing the algorithm from getting trapped in local optima. In experiments, a thorough investigation is undertaken on the characteristics, parameters, and time cost of the MGO algorithm to enhance the understanding of MGO. Subsequently, MGO is compared with 10 original and advanced CEC 2017 and CEC 2022 algorithms to verify its performance advantages. Lastly, this paper applies MGO to four real-world engineering problems to validate its effectiveness and superiority in practical scenarios. The results demonstrate that MGO is a promising algorithm for tackling real challenges. The source codes of the MGO are available at https:\/\/aliasgharheidari.com\/MGO.html and other websites.<\/jats:p>","DOI":"10.1093\/jcde\/qwae080","type":"journal-article","created":{"date-parts":[[2024,9,21]],"date-time":"2024-09-21T02:55:06Z","timestamp":1726887306000},"page":"184-221","source":"Crossref","is-referenced-by-count":54,"title":["The moss growth optimization (MGO): concepts and performance"],"prefix":"10.1093","volume":"11","author":[{"given":"Boli","family":"Zheng","sequence":"first","affiliation":[{"name":"Key Laboratory of Intelligent Informatics for Safety & Emergency of Zhejiang Province, Wenzhou University , Wenzhou 325035 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7027-6542","authenticated-orcid":false,"given":"Yi","family":"Chen","sequence":"additional","affiliation":[{"name":"Key Laboratory of Intelligent Informatics for Safety & Emergency of Zhejiang Province, Wenzhou University , Wenzhou 325035 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chaofan","family":"Wang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Intelligent Informatics for Safety & Emergency of Zhejiang Province, Wenzhou University , Wenzhou 325035 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ali Asghar","family":"Heidari","sequence":"additional","affiliation":[{"name":"School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran , Tehran, 1439957131 ,","place":["Iran"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4698-2965","authenticated-orcid":false,"given":"Lei","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Computer Science, Sichuan University , Sichuan, Chengdu 610065 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7714-9693","authenticated-orcid":false,"given":"Huiling","family":"Chen","sequence":"additional","affiliation":[{"name":"Key Laboratory of Intelligent Informatics for Safety & Emergency of Zhejiang Province, Wenzhou University , Wenzhou 325035 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2024,9,20]]},"reference":[{"key":"2024100912555978800_bib1","doi-asserted-by":"publisher","first-page":"484","DOI":"10.1016\/j.eswa.2017.07.043","article-title":"An improved opposition-based sine cosine algorithm for global optimization","volume":"90","author":"Abd\u00a0Elaziz","year":"2017","journal-title":"Expert Systems with Applications"},{"key":"2024100912555978800_bib2","doi-asserted-by":"publisher","first-page":"11675","DOI":"10.1007\/s10462-023-10446-y","article-title":"Spider wasp optimizer: A novel meta-heuristic optimization algorithm","volume":"56","author":"Abdel-Basset","year":"2023","journal-title":"Artificial Intelligence Review"},{"key":"2024100912555978800_bib3","doi-asserted-by":"publisher","DOI":"10.13140\/rg.2.2.32347.85284","article-title":"Problem definition and evaluation criteria for the CEC'2022 competition on dynamic multimodal optimization","author":"Ahrari","year":"2022"},{"key":"2024100912555978800_bib4","doi-asserted-by":"publisher","first-page":"307","DOI":"10.1007\/s00500-008-0323-y","article-title":"KEEL: A software tool to assess evolutionary algorithms for data mining problems","volume":"13","author":"Alcal\u00e1-Fdez","year":"2009","journal-title":"Soft Computing"},{"key":"2024100912555978800_bib5","doi-asserted-by":"publisher","first-page":"342","DOI":"10.1016\/j.neunet.2023.08.035","article-title":"Metaheuristics optimization-based ensemble of deep neural networks for Mpox disease detection","volume":"167","author":"Asif","year":"2023","journal-title":"Neural Networks"},{"key":"2024100912555978800_bib6","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1023\/A:1015059928466","article-title":"Evolution strategies\u2013a comprehensive introduction","volume":"1","author":"Beyer","year":"2002","journal-title":"Natural Computing"},{"key":"2024100912555978800_bib7","doi-asserted-by":"publisher","first-page":"4049","DOI":"10.1007\/s11831-022-09730-x","article-title":"Hybrid meta-heuristic algorithms for optimal sizing of hybrid renewable energy system: A review of the state-of-the-art","volume":"29","author":"Bouaouda","year":"2022","journal-title":"Archives of Computational Methods in Engineering"},{"key":"2024100912555978800_bib8","doi-asserted-by":"publisher","first-page":"4438","DOI":"10.1038\/s41598-017-04848-6","article-title":"Moss survival through in situ cryptobiosis after six centuries of glacier burial","volume":"7","author":"Cannone","year":"2017","journal-title":"Scientific Reports"},{"key":"2024100912555978800_bib9","doi-asserted-by":"publisher","first-page":"3099","DOI":"10.1109\/JIOT.2020.3033473","article-title":"RFID reader anticollision based on distributed parallel particle swarm optimization","volume":"8","author":"Cao","year":"2021","journal-title":"IEEE Internet of Things Journal"},{"key":"2024100912555978800_bib10","doi-asserted-by":"publisher","first-page":"78","DOI":"10.1109\/MNET.011.1900536","article-title":"A many-objective optimization model of industrial internet of things based on private blockchain","volume":"34","author":"Cao","year":"2020","journal-title":"IEEE Network"},{"key":"2024100912555978800_bib11","doi-asserted-by":"publisher","first-page":"100864","DOI":"10.1016\/j.swevo.2021.100864","article-title":"A memetic algorithm based on two_Arch2 for multi-depot heterogeneous-vehicle capacitated Arc routing problem","volume":"63","author":"Cao","year":"2021","journal-title":"Swarm and Evolutionary Computation"},{"key":"2024100912555978800_bib12","doi-asserted-by":"publisher","first-page":"100626","DOI":"10.1016\/j.swevo.2019.100626","article-title":"Applying graph-based differential grouping for multiobjective large-scale optimization","volume":"53","author":"Cao","year":"2020","journal-title":"Swarm and Evolutionary Computation"},{"key":"2024100912555978800_bib13","doi-asserted-by":"publisher","first-page":"3597","DOI":"10.1109\/TII.2019.2952565","article-title":"Multiobjective 3-D topology optimization of next-generation wireless data center network","volume":"16","author":"Cao","year":"2019","journal-title":"IEEE Transactions on Industrial Informatics"},{"key":"2024100912555978800_bib14","doi-asserted-by":"publisher","first-page":"113018","DOI":"10.1016\/j.eswa.2019.113018","article-title":"An efficient double adaptive random spare reinforced whale optimization algorithm","volume":"154","author":"Chen","year":"2020","journal-title":"Expert Systems with Applications"},{"key":"2024100912555978800_bib15","doi-asserted-by":"publisher","first-page":"241","DOI":"10.1109\/TEVC.2011.2173577","article-title":"Particle swarm optimization with an aging leader and challengers","volume":"17","author":"Chen","year":"2012","journal-title":"IEEE Transactions on Evolutionary Computation"},{"key":"2024100912555978800_bib16","doi-asserted-by":"publisher","first-page":"339","DOI":"10.1146\/annurev.genet.39.073003.110214","article-title":"The moss physcomitrella patens","volume":"39","author":"Cove","year":"2005","journal-title":"Annual Review of Genetics"},{"key":"2024100912555978800_bib17","doi-asserted-by":"publisher","first-page":"110011","DOI":"10.1016\/j.knosys.2022.110011","article-title":"Coati Optimization Algorithm: A new bio-inspired metaheuristic algorithm for solving optimization problems","volume":"259","author":"Dehghani","year":"2023","journal-title":"Knowledge-Based Systems"},{"key":"2024100912555978800_bib18","doi-asserted-by":"publisher","first-page":"934","DOI":"10.1093\/jcde\/qwad029","article-title":"The applications of hybrid approach combining exact method and evolutionary algorithm in combinatorial optimization","volume":"10","author":"Duan","year":"2023","journal-title":"Journal of Computational Design and Engineering"},{"key":"2024100912555978800_bib19","doi-asserted-by":"publisher","first-page":"101004","DOI":"10.1016\/j.segan.2023.101004","article-title":"An initialization-free distributed algorithm for dynamic economic dispatch problems in microgrid: Modeling, optimization and analysis","volume":"34","author":"Duan","year":"2023","journal-title":"Sustainable Energy, Grids and Networks"},{"key":"2024100912555978800_bib20","doi-asserted-by":"publisher","first-page":"122147","DOI":"10.1016\/j.eswa.2023.122147","article-title":"Greylag goose optimization: Nature-inspired optimization algorithm","volume":"238","author":"El-kenawy","year":"2024","journal-title":"Expert Systems with Applications"},{"key":"2024100912555978800_bib21","doi-asserted-by":"publisher","first-page":"106966","DOI":"10.1016\/j.compbiomed.2023.106966","article-title":"Optimized deep learning architecture for brain tumor classification using improved Hunger Games search algorithm","volume":"160","author":"Emam","year":"2023","journal-title":"Computers in Biology and Medicine"},{"key":"2024100912555978800_bib22","doi-asserted-by":"publisher","first-page":"357","DOI":"10.1016\/j.isatra.2022.08.025","article-title":"Modified bald eagle search algorithm for lithium-ion battery model parameters extraction","volume":"134","author":"Ferahtia","year":"2023","journal-title":"ISA Transactions"},{"key":"2024100912555978800_bib23","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1007\/s00366-011-0241-y","article-title":"Cuckoo search algorithm: A metaheuristic approach to solve structural optimization problems","volume":"29","author":"Gandomi","year":"2013","journal-title":"Engineering with Computers"},{"key":"2024100912555978800_bib24","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1177\/003754970107600201","article-title":"A new heuristic optimization algorithm: Harmony search","volume":"76","author":"Geem","year":"2001","journal-title":"Simulation"},{"key":"2024100912555978800_bib25","doi-asserted-by":"publisher","first-page":"177","DOI":"10.1016\/j.asoc.2014.02.006","article-title":"Exchange market algorithm","volume":"19","author":"Ghorbani","year":"2014","journal-title":"Applied Soft Computing"},{"key":"2024100912555978800_bib26","doi-asserted-by":"publisher","first-page":"107769","DOI":"10.1016\/j.compbiomed.2023.107769","article-title":"Multi-threshold image segmentation based on an improved salp swarm algorithm: Case study of breast cancer pathology images","volume":"168","author":"Guo","year":"2024","journal-title":"Computers in Biology and Medicine"},{"key":"2024100912555978800_bib27","doi-asserted-by":"publisher","first-page":"159","DOI":"10.1162\/106365601750190398","article-title":"Completely derandomized self-adaptation in evolution strategies","volume":"9","author":"Hansen","year":"2001","journal-title":"Evolutionary Computation"},{"key":"2024100912555978800_bib28","doi-asserted-by":"publisher","first-page":"655","DOI":"10.1093\/jcde\/qwad006","article-title":"Salp swarm algorithm with iterative mapping and local escaping for multi-level threshold image segmentation: A skin cancer dermoscopic case study","volume":"10","author":"Hao","year":"2023","journal-title":"Journal of Computational Design and Engineering"},{"key":"2024100912555978800_bib29","doi-asserted-by":"crossref","DOI":"10.2514\/6.2005-1897","article-title":"A comparison of particle swarm optimization and the genetic algorithm","volume-title":"46th AIAA\/ASME\/ASCE\/AHS\/ASC Structures, Structural Dynamics and Materials Conference","author":"Hassan","year":"2005"},{"key":"2024100912555978800_bib30","doi-asserted-by":"publisher","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 Transactions on Evolutionary Computation"},{"key":"2024100912555978800_bib31","doi-asserted-by":"publisher","first-page":"1129","DOI":"10.1126\/science.1061457","article-title":"Molecular evidence for the early colonization of land by fungi and plants","volume":"293","author":"Heckman","year":"2001","journal-title":"Science"},{"key":"2024100912555978800_bib32","doi-asserted-by":"publisher","first-page":"105521","DOI":"10.1016\/j.asoc.2019.105521","article-title":"Efficient boosted grey wolf optimizers for global search and kernel extreme learning machine training","volume":"81","author":"Heidari","year":"2019","journal-title":"Applied Soft Computing"},{"key":"2024100912555978800_bib33","doi-asserted-by":"publisher","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":"2024100912555978800_bib34","doi-asserted-by":"publisher","first-page":"66","DOI":"10.1038\/scientificamerican0792-66","article-title":"Genetic algorithms","volume":"267","author":"Holland","year":"1992","journal-title":"Scientific American"},{"key":"2024100912555978800_bib35","doi-asserted-by":"publisher","first-page":"1363","DOI":"10.1093\/jcde\/qwad053","article-title":"Enhancing feature selection with GMSMFO: A global optimization algorithm for machine learning with application to intrusion detection","volume":"10","author":"Hussein","year":"2023","journal-title":"Journal of Computational Design and Engineering"},{"key":"2024100912555978800_bib36","doi-asserted-by":"publisher","first-page":"435","DOI":"10.1162\/1063656043138897","article-title":"LARES: An artificial chemical process approach for optimization","volume":"12","author":"Irizarry","year":"2004","journal-title":"Evolutionary Computation"},{"key":"2024100912555978800_bib37","doi-asserted-by":"publisher","first-page":"358","DOI":"10.1016\/j.jenvman.2019.04.117","article-title":"Genetic and firefly metaheuristic algorithms for an optimized neuro-fuzzy prediction modeling of wildfire probability","volume":"243","author":"Jaafari","year":"2019","journal-title":"Journal of Environmental Management"},{"key":"2024100912555978800_bib38","doi-asserted-by":"publisher","first-page":"72","DOI":"10.1016\/j.asoc.2015.03.035","article-title":"Ions motion algorithm for solving optimization problems","volume":"32","author":"Javidy","year":"2015","journal-title":"Applied Soft Computing"},{"key":"2024100912555978800_bib39","doi-asserted-by":"publisher","first-page":"111402","DOI":"10.1016\/j.knosys.2024.111402","article-title":"Guided learning strategy: A novel update mechanism for metaheuristic algorithms design and improvement","volume":"286","author":"Jia","year":"2024","journal-title":"Knowledge-Based Systems"},{"key":"2024100912555978800_bib40","doi-asserted-by":"publisher","first-page":"1196","DOI":"10.1111\/1365-2435.12606","article-title":"Air humidity thresholds trigger active moss spore release to extend dispersal in space and time","volume":"30","author":"Johansson","year":"2016","journal-title":"Functional Ecology"},{"key":"2024100912555978800_bib41","doi-asserted-by":"publisher","first-page":"523","DOI":"10.1038\/hdy.2016.13","article-title":"The effects of quantitative fecundity in the haploid stage on reproductive success and diploid fitness in the aquatic peat moss Sphagnum macrophyllum","volume":"116","author":"Johnson","year":"2016","journal-title":"Heredity"},{"key":"2024100912555978800_bib42","volume-title":"An idea based on honey bee swarm for numerical optimization","author":"Karaboga","year":"2005"},{"key":"2024100912555978800_bib43","doi-asserted-by":"publisher","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":"2024100912555978800_bib44","doi-asserted-by":"crossref","DOI":"10.1109\/ICNN.1995.488968","article-title":"Particle swarm optimization","volume-title":"Proceedings of ICNN'95-international Conference on Neural Networks","author":"Kennedy","year":"1995"},{"key":"2024100912555978800_bib45","doi-asserted-by":"publisher","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":"2024100912555978800_bib46","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1007\/BF00175355","article-title":"Genetic programming as a means for programming computers by natural selection","volume":"4","author":"Koza","year":"1994","journal-title":"Statistics and Computing"},{"key":"2024100912555978800_bib47","doi-asserted-by":"publisher","first-page":"983","DOI":"10.1109\/TEC.2017.2669518","article-title":"Single sensor-based MPPT of partially shaded PV system for battery charging by using cauchy and gaussian sine cosine optimization","volume":"32","author":"Kumar","year":"2017","journal-title":"IEEE Transactions on Energy Conversion"},{"key":"2024100912555978800_bib48","doi-asserted-by":"publisher","first-page":"949","DOI":"10.1093\/jcde\/qwac040","article-title":"HFMOEA: A hybrid framework for multi-objective feature selection","volume":"9","author":"Kundu","year":"2022","journal-title":"Journal of Computational Design and Engineering"},{"key":"2024100912555978800_bib49","doi-asserted-by":"publisher","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":"2024100912555978800_bib50","doi-asserted-by":"publisher","first-page":"107736","DOI":"10.1016\/j.isci.2023.107736","article-title":"Advanced slime mould algorithm incorporating differential evolution and Powell mechanism for engineering design","volume":"26","author":"Li","year":"2023","journal-title":"Iscience"},{"key":"2024100912555978800_bib51","doi-asserted-by":"publisher","first-page":"122638","DOI":"10.1016\/j.eswa.2023.122638","article-title":"Human evolutionary optimization algorithm","volume":"241","author":"Lian","year":"2024","journal-title":"Expert Systems with Applications"},{"key":"2024100912555978800_bib52","doi-asserted-by":"publisher","first-page":"5052","DOI":"10.1109\/TPWRS.2018.2812711","article-title":"A hybrid bat algorithm for economic dispatch with random wind power","volume":"33","author":"Liang","year":"2018","journal-title":"IEEE Transactions on Power Systems"},{"key":"2024100912555978800_bib53","doi-asserted-by":"publisher","first-page":"R1175","DOI":"10.1016\/j.cub.2023.09.042","article-title":"Mosses","volume":"33","author":"Lueth","year":"2023","journal-title":"Current Biology"},{"key":"2024100912555978800_bib54","doi-asserted-by":"publisher","first-page":"14690","DOI":"10.1109\/ACCESS.2024.3351468","article-title":"The optimization of carbon emission prediction in low carbon energy economy under big data","volume":"12","author":"Luo","year":"2024","journal-title":"IEEE Access"},{"key":"2024100912555978800_bib55","doi-asserted-by":"publisher","first-page":"10312","DOI":"10.1038\/s41598-023-37537-8","article-title":"Mother optimization algorithm: A new human-based metaheuristic approach for solving engineering optimization","volume":"13","author":"Matou\u0161ov\u00e1","year":"2023","journal-title":"Scientific Reports"},{"key":"2024100912555978800_bib56","doi-asserted-by":"publisher","first-page":"128604","DOI":"10.1016\/j.biortech.2023.128604","article-title":"Metaheuristic optimization of data preparation and machine learning hyperparameters for prediction of dynamic methane production","volume":"372","author":"Meola","year":"2023","journal-title":"Bioresource Technology"},{"key":"2024100912555978800_bib57","doi-asserted-by":"publisher","first-page":"228","DOI":"10.1016\/j.knosys.2015.07.006","article-title":"Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm","volume":"89","author":"Mirjalili","year":"2015","journal-title":"Knowledge-Based Systems"},{"key":"2024100912555978800_bib58","doi-asserted-by":"publisher","first-page":"120","DOI":"10.1016\/j.knosys.2015.12.022","article-title":"SCA: A sine cosine algorithm for solving optimization problems","volume":"96","author":"Mirjalili","year":"2016","journal-title":"Knowledge-Based Systems"},{"key":"2024100912555978800_bib59","doi-asserted-by":"publisher","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":"Advances in Engineering Software"},{"key":"2024100912555978800_bib60","doi-asserted-by":"publisher","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":"2024100912555978800_bib61","doi-asserted-by":"publisher","first-page":"1019","DOI":"10.1016\/j.asoc.2017.09.039","article-title":"Hybridizing sine cosine algorithm with differential evolution for global optimization and object tracking","volume":"62","author":"Nenavath","year":"2018","journal-title":"Applied Soft Computing"},{"key":"2024100912555978800_bib62","doi-asserted-by":"publisher","first-page":"1065","DOI":"10.1038\/s41598-022-04923-7","article-title":"Proposing a hybrid metaheuristic optimization algorithm and machine learning model for energy use forecast in non-residential buildings","volume":"12","author":"Ngo","year":"2022","journal-title":"Scientific Reports"},{"key":"2024100912555978800_bib63","doi-asserted-by":"publisher","first-page":"1731","DOI":"10.1007\/s00366-020-01127-3","article-title":"A novel upgraded bat algorithm based on cuckoo search and sugeno inertia weight for large scale and constrained engineering design optimization problems","volume":"38","author":"Pathak","year":"2022","journal-title":"Engineering with Computers"},{"key":"2024100912555978800_bib64","doi-asserted-by":"publisher","first-page":"261\u2212278","DOI":"10.1016\/j.jare.2023.01.014","article-title":"Hierarchical Harris hawks optimizer for feature selection","volume":"53","author":"Peng","year":"2023","journal-title":"Journal of Advanced Research"},{"key":"2024100912555978800_bib65","doi-asserted-by":"publisher","first-page":"2200","DOI":"10.1093\/jcde\/qwad093","article-title":"Multi-threshold remote sensing image segmentation with improved ant colony optimizer with salp foraging","volume":"10","author":"Qian","year":"2023","journal-title":"Journal of Computational Design and Engineering"},{"key":"2024100912555978800_bib66","doi-asserted-by":"publisher","first-page":"122316","DOI":"10.1016\/j.eswa.2023.122316","article-title":"A multi-level thresholding image segmentation method using hybrid Arithmetic Optimization and Harris Hawks Optimizer algorithms","volume":"241","author":"Qiao","year":"2024","journal-title":"Expert Systems with Applications"},{"key":"2024100912555978800_bib67","first-page":"13187\u221213257","article-title":"An exhaustive review of the metaheuristic algorithms for search and optimization: Taxonomy, applications, and open challenges","volume":"56(11)","author":"Rajwar","year":"2023","journal-title":"Artificial Intelligence Review"},{"key":"2024100912555978800_bib68","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1016\/j.cad.2010.12.015","article-title":"Teaching\u2013learning-based optimization: A novel method for constrained mechanical design optimization problems","volume":"43","author":"Rao","year":"2011","journal-title":"Computer-aided Design"},{"key":"2024100912555978800_bib69","doi-asserted-by":"publisher","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":"Information Sciences"},{"key":"2024100912555978800_bib70","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1111\/j.1438-8677.1998.tb00670.x","article-title":"Development, genetics and molecular biology of mosses","volume":"111","author":"Reski","year":"1998","journal-title":"Botanica Acta"},{"key":"2024100912555978800_bib71","first-page":"391","article-title":"Shape optimization with surface-mapped CPPNs","volume":"21","author":"Richards","year":"2016","journal-title":"IEEE Transactions on Evolutionary Computation"},{"key":"2024100912555978800_bib72","doi-asserted-by":"publisher","first-page":"431","DOI":"10.1038\/nature11330","article-title":"Sex-specific volatile compounds influence microarthropod-mediated fertilization of moss","volume":"489","author":"Rosenstiel","year":"2012","journal-title":"Nature"},{"key":"2024100912555978800_bib73","doi-asserted-by":"publisher","first-page":"120367","DOI":"10.1016\/j.eswa.2023.120367","article-title":"Self-adaptive moth flame optimizer combined with crossover operator and fibonacci search strategy for COVID-19 CT image segmentation","volume":"227","author":"Sahoo","year":"2023","journal-title":"Expert Systems with Applications"},{"key":"2024100912555978800_bib74","doi-asserted-by":"publisher","first-page":"1430","DOI":"10.1104\/pp.010786","article-title":"The moss physcomitrella patens, now and then","volume":"127","author":"Schaefer","year":"2001","journal-title":"Plant Physiology"},{"key":"2024100912555978800_bib75","doi-asserted-by":"crossref","DOI":"10.1201\/9781420036268","volume-title":"Handbook of Parametric and Nonparametric Statistical Procedures","author":"Sheskin","year":"2003"},{"key":"2024100912555978800_bib76","doi-asserted-by":"publisher","first-page":"702","DOI":"10.1109\/TEVC.2008.919004","article-title":"Biogeography-based optimization","volume":"12","author":"Simon","year":"2008","journal-title":"IEEE Transactions on Evolutionary Computation"},{"key":"2024100912555978800_bib77","doi-asserted-by":"publisher","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":"Journal of Global Optimization"},{"key":"2024100912555978800_bib78","doi-asserted-by":"publisher","first-page":"183","DOI":"10.1016\/j.neucom.2023.02.010","article-title":"RIME: A physics-based optimization","volume":"532","author":"Su","year":"2023","journal-title":"Neurocomputing"},{"key":"2024100912555978800_bib79","doi-asserted-by":"publisher","first-page":"5760","DOI":"10.1109\/JIOT.2019.2937110","article-title":"Low-latency and resource-efficient service function chaining orchestration in network function virtualization","volume":"7","author":"Sun","year":"2019","journal-title":"IEEE Internet of Things Journal"},{"key":"2024100912555978800_bib80","doi-asserted-by":"publisher","first-page":"7550","DOI":"10.1109\/TVT.2018.2828651","article-title":"Bus-trajectory-based street-centric routing for message delivery in urban vehicular ad hoc networks","volume":"67","author":"Sun","year":"2018","journal-title":"IEEE Transactions on Vehicular Technology"},{"key":"2024100912555978800_bib81","doi-asserted-by":"publisher","first-page":"1688","DOI":"10.1007\/s10489-018-1334-8","article-title":"Improved whale optimization algorithm for feature selection in Arabic sentiment analysis","volume":"49","author":"Tubishat","year":"2019","journal-title":"Applied Intelligence"},{"key":"2024100912555978800_bib82","volume-title":"Grey Wolf, Firefly and Bat Algorithms: Three Widespread Algorithms That Do Not Contain any Novelty. International Conference on Swarm Intelligence","author":"Villal\u00f3n","year":"2020"},{"key":"2024100912555978800_bib83","doi-asserted-by":"publisher","first-page":"2462891","DOI":"10.1155\/2017\/2462891","article-title":"An improved hybrid algorithm based on biogeography\/complex and metropolis for many-objective optimization","volume":"2017","author":"Wang","year":"2017","journal-title":"Mathematical Problems in Engineering"},{"key":"2024100912555978800_bib84","first-page":"6676\u22126689","article-title":"Differential evolution with duplication analysis for feature selection in classification","volume":"53(10)","author":"Wang","year":"2022","journal-title":"IEEE Transactions on Cybernetics"},{"key":"2024100912555978800_bib85","doi-asserted-by":"publisher","first-page":"107469","DOI":"10.1016\/j.est.2023.107469","article-title":"Techno-economic analysis and optimization of hybrid energy systems based on hydrogen storage for sustainable energy utilization by a biological-inspired optimization algorithm","volume":"66","author":"Wang","year":"2023","journal-title":"Journal of Energy Storage"},{"key":"2024100912555978800_bib86","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1093\/jcde\/qwae004","article-title":"Boosting aquila optimizer by marine predators algorithm for combinatorial optimization","volume":"11","author":"Wang","year":"2024","journal-title":"Journal of Computational Design and Engineering"},{"key":"2024100912555978800_bib87","doi-asserted-by":"publisher","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":"2024100912555978800_bib88","article-title":"Problem definitions and evaluation criteria for the CEC 2017 competition on constrained real-parameter optimization","volume-title":"National University of Defense Technology, Changsha, Hunan, PR China and Kyungpook National University, Daegu, South Korea and Nanyang Technological University, Singapore, Technical Report","author":"Wu","year":"2017"},{"key":"2024100912555978800_bib89","doi-asserted-by":"publisher","first-page":"126","DOI":"10.1016\/j.asoc.2018.02.042","article-title":"A multi-swarm particle swarm optimization algorithm based on dynamical topology and purposeful detecting","volume":"67","author":"Xia","year":"2018","journal-title":"Applied Soft Computing"},{"key":"2024100912555978800_bib90","article-title":"General framework of artificial physics optimization algorithm","volume-title":"2009 world congress on Nature & Biologically Inspired Computing (NaBIC)","author":"Xie","year":"2009"},{"key":"2024100912555978800_bib91","doi-asserted-by":"publisher","first-page":"0039","DOI":"10.34133\/plantphenomics.0039","article-title":"A novel feature selection strategy based on salp swarm algorithm for plant disease detection","volume":"5","author":"Xie","year":"2023","journal-title":"Plant Phenomics"},{"key":"2024100912555978800_bib92","doi-asserted-by":"crossref","first-page":"108835","DOI":"10.1016\/j.cie.2022.108835","article-title":"Dynamic pickup and delivery problem with transshipments and LIFO constraints","volume":"175","author":"Xu","year":"2023","journal-title":"Computers & Industrial Engineering"},{"key":"2024100912555978800_bib93","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-642-04944-6_14","article-title":"Firefly algorithms for multimodal optimization","volume-title":"International symposium on Stochastic Algorithms","author":"Yang","year":"2009"},{"key":"2024100912555978800_bib94","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1007\/978-3-642-12538-6_6","article-title":"A new metaheuristic bat-inspired algorithm","volume-title":"Nature Inspired Cooperative Strategies for Optimization (NICSO 2010)","author":"Yang","year":"2010"},{"key":"2024100912555978800_bib95","doi-asserted-by":"publisher","first-page":"464","DOI":"10.1108\/02644401211235834","article-title":"Bat algorithm: A novel approach for global engineering optimization","volume":"29","author":"Yang","year":"2012","journal-title":"Engineering Computations"},{"key":"2024100912555978800_bib96","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1109\/4235.771163","article-title":"Evolutionary programming made faster","volume":"3","author":"Yao","year":"1999","journal-title":"IEEE Transactions on Evolutionary Computation"},{"key":"2024100912555978800_bib97","first-page":"1","article-title":"Energy saving in flow-shop scheduling management: An improved multiobjective model based on grey wolf optimization algorithm","volume":"2020","author":"Yin","year":"2020","journal-title":"Mathematical Problems in Engineering"},{"key":"2024100912555978800_bib98","doi-asserted-by":"publisher","first-page":"101462","DOI":"10.1016\/j.swevo.2023.101462","article-title":"A survey of meta-heuristic algorithms in optimization of space scale expansion","volume":"84","author":"Zhang","year":"2024","journal-title":"Swarm and Evolutionary Computation"},{"key":"2024100912555978800_bib99","doi-asserted-by":"publisher","first-page":"283","DOI":"10.1016\/j.knosys.2018.08.030","article-title":"Atom search optimization and its application to solve a hydrogeologic parameter estimation problem","volume":"163","author":"Zhao","year":"2019","journal-title":"Knowledge-Based Systems"},{"key":"2024100912555978800_bib100","doi-asserted-by":"publisher","first-page":"122200","DOI":"10.1016\/j.eswa.2023.122200","article-title":"Electric eel foraging optimization: A new bio-inspired optimizer for engineering applications","volume":"238","author":"Zhao","year":"2024","journal-title":"Expert Systems with Applications"},{"key":"2024100912555978800_bib101","doi-asserted-by":"publisher","first-page":"116446","DOI":"10.1016\/j.cma.2023.116446","article-title":"Quadratic Interpolation Optimization (QIO): A new optimization algorithm based on generalized quadratic interpolation and its applications to real-world engineering problems","volume":"417","author":"Zhao","year":"2023","journal-title":"Computer Methods in Applied Mechanics 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\/qwae080\/59215484\/qwae080.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/jcde\/advance-article-pdf\/doi\/10.1093\/jcde\/qwae080\/59647770\/qwae080.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/jcde\/advance-article-pdf\/doi\/10.1093\/jcde\/qwae080\/59647770\/qwae080.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,9]],"date-time":"2024-10-09T12:56:31Z","timestamp":1728478591000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/jcde\/article\/11\/5\/184\/7762972"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,31]]},"references-count":101,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2024,8,31]]}},"URL":"https:\/\/doi.org\/10.1093\/jcde\/qwae080","relation":{},"ISSN":["2288-5048"],"issn-type":[{"value":"2288-5048","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2024,10]]},"published":{"date-parts":[[2024,8,31]]}}}