Abstract
In this paper, to keep the researchers interested in nature-inspired algorithms and optimization problems, a comprehensive survey of the group search optimizer (GSO) algorithm is introduced with detailed discussions. GSO is a nature-inspired optimization algorithm introduced by He et al. (IEEE Trans Evol Comput 13:973–990, 2009) to solve several different optimization problems. It is inspired by animal searching behavior in real life. This survey focuses on the applications of the GSO algorithm and its variants and results from the year of its suggestion (2009) to now (2020). GSO algorithm is used to discover the best solution over a set of candidate solution to solve any optimization problem by determining the minimum or maximum objective function for a specific problem. Meta-heuristic optimizations, nature-inspired algorithms, have become an interesting area because of their rule in solving various decision-making problems. The general procedures of the GSO algorithm are explained alongside with the algorithm variants such as basic versions, discrete versions, and modified versions. Moreover, the applications of the GSO algorithm are given in detail such as benchmark function, classification, networking, engineering, and other problems. Finally, according to the analyzed papers published in the literature by the all publishers such as IEEE, Elsevier, and Springer, the GSO algorithm is mostly used in solving various optimization problems. In addition, it got comparative and promising results compared to other similar published optimization algorithm.
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.Change history
22 July 2024
This article has been retracted. Please see the Retraction Notice for more detail: https://doi.org/10.1007/s00521-024-10103-7
References
Bolaji AL, Al-Betar MA, Awadallah MA, Khader AT, Abualigah LM (2016) A comprehensive review: Krill herd algorithm (kh) and its applications. Appl Soft Comput 49:437–446
Shehab M, Khader AT, Al-Betar MA, Abualigah LM (2017) Hybridizing cuckoo search algorithm with hill climbing for numerical optimization problems. In: 8th International conference on information technology (ICIT). IEEE 2017, pp 36–43
Abualigah LM, Sawaie AM, Khader AT, Rashaideh H, Al-Betar MA, Shehab M (2017) \(\beta\)-hill climbing technique for the text document clustering, New Trends in Information Technology (NTIT)–2017. p 60
Glover F, Kochenberger GA (1996) Critical event tabu search for multidimensional knapsack problems. In: Meta-heuristics, Springer, New York, pp 407–427
Kirkpatrick S, Gelatt CD, Vecchi MP (1983) Optimization by simulated annealing. Science 220:671–680
Abualigah L, Shehab M, Alshinwan M, Alabool H (2019) Salp swarm algorithm: a comprehensive survey. Neural Comput Appl 1–21
Abualigah L (2020) Multi-verse optimizer algorithm: a comprehensive survey of its results, variants, and applications. Neural Comput Appl 1–21
Han K-H, Kim J-H (2002) Quantum-inspired evolutionary algorithm for a class of combinatorial optimization. IEEE Trans Evolut Comput 6:580–593
Abualigah L, Diabat A (2020) A novel hybrid Antlion optimization algorithm for multi-objective task scheduling problems in cloud computing environments. Cluster Comput 1–19
Abualigah LMQ (2019) Feature selection and enhanced krill herd algorithm for text document clustering. Springer, New York
Abualigah LM, Khader AT, Hanandeh ES (2018) A hybrid strategy for krill herd algorithm with harmony search algorithm to improve the data clustering. Intell Decision Technol 12:3–14
Shi Y (2011) Brain storm optimization algorithm. In: International conference in swarm intelligence, Springer, New York, pp 303–309
Mirjalili S, Gandomi AH, Mirjalili SZ, Saremi S, Faris H, Mirjalili SM (2017) Salp swarm algorithm: a bio-inspired optimizer for engineering design problems. Adv Eng Softw 114:163–191
Rashaideh H, Sawaie A, Al-Betar MA, Abualigah LM, Al-Laham MM, Ra’ed M, Braik M (2018) A grey wolf optimizer for text document clustering. J Intell Syst 29:814–830
Abualigah LM, Khader AT (2017) Unsupervised text feature selection technique based on hybrid particle swarm optimization algorithm with genetic operators for the text clustering. J Supercomput 73:4773–4795
Shehab M, Abualigah L, Al Hamad H, Alabool H, Alshinwan M, Khasawneh AM (2019) Moth–flame optimization algorithm: variants and applications. Neural Comput Appl 1–26
Rashedi E, Nezamabadi-Pour H, Saryazdi S (2009) Gsa: a gravitational search algorithm. Inf Sci 179:2232–2248
Mirjalili S, Lewis A (2016) The whale optimization algorithm. Adv Eng Softw 95:51–67
Alomari OA, Khader AT, Al-Betar MA, Abualigah LM (2017) Gene selection for cancer classification by combining minimum redundancy maximum relevancy and bat-inspired algorithm. Int J Data Min Bioinform 19:32–51
Abualigah L, Shehab M, Alshinwan M, Mirjalili S, Abd Elaziz M (2020) Ant lion optimizer: a comprehensive survey of its variants and applications. Arch Comput Methods Eng
Shehab M, Daoud MS, AlMimi HM, Abualigah LM, Khader AT (2019) Hybridising cuckoo search algorithm for extracting the ODF maxima in spherical harmonic representation. Int J Bio-Inspired Comput 14:190–199
Cheng M-Y, Prayogo D (2014) Symbiotic organisms search: a new metaheuristic optimization algorithm. Comput Struct 139:98–112
He S, Wu QH, Saunders J (2009) Group search optimizer: an optimization algorithm inspired by animal searching behavior. IEEE Trans Evol Comput 13:973–990
Mustard D (1964) Numerical integration over the n-dimensional spherical shell. Math Comput 18:578–589
Giraldeau L-A, Lefebvre L (1986) Exchangeable producer and scrounger roles in a captive flock of feral pigeons: a case for the skill pool effect. Anim Behav 34:797–803
Barnard CJ, Sibly RM (1981) Producers and scroungers: a general model and its application to captive flocks of house sparrows. Anim Behav 29:543–550
Xing B, Gao W.-J. (2014) Group search optimizer algorithm. In: Innovative computational intelligence: a rough guide to 134 clever algorithms, Springer, New York, pp 171–176
Fang J, Cui Z, Cai X, Zeng J (2010) A hybrid group search optimizer with metropolis rule. In: Proceedings of the 2010 international conference on modelling, identification and control, IEEE, pp 556–561
Shen H, Zhu Y, Zou W, Zhu Z (2011) Group search optimizer algorithm for constrained optimization. In: International workshop on computer science for environmental engineering and ecoinformatics, Springer, New York, pp 48–53
Fang Z, Chen D (2011) New group search optimizer algorithm based on chaotic searching. J Comput Appl 31:657–660
Liao H, Chen H, Wu Q, Bazargan M, Ji Z (2012) Group search optimizer for power system economic dispatch. In: International conference in swarm intelligence, Springer, New York, pp 253–260
Chen D, Wang J, Zou F, Hou W, Zhao C (2012) An improved group search optimizer with operation of quantum-behaved swarm and its application. Appl Soft Comput 12:712–725
Wang L, Zhong X, Liu M (2012) A novel group search optimizer for multi-objective optimization. Expert Syst Appl 39:2939–2946
Liu F, Li LJ, Yuan B (2012) Multi-objective optimal design of frame structures with group search optimizer. In: Applied mechanics and materials, volume 121, Trans Tech Publ, pp 968–975
Li Y, Li M, Ji Z, Wu QH (2013) Optimal power flow using group search optimizer with intraspecific competition and Lévy walk. In: IEEE symposium on swarm intelligence (SIS). IEEE, pp 256–262
Zheng X-W, Lu D-J, Chen Z-H (2014) A self-adaptive group search optimizer with elitist strategy. In: IEEE congress on evolutionary computation (CEC). IEEE, pp 2033–2039
Chen J, Zheng J, Liu Y, Wu Q (2014) Dynamic economic dispatch with wind power penetration using group search optimizer with adaptive strategies. In: IEEE PES innovative smart grid technologies, Europe, IEEE, pp 1–6
Zhang K, Gu X (2014) A fast global group search optimizer algorithm. In: 2014 IEEE international conference on information and automation (ICIA), IEEE, pp 59–64
Jin J, Li L, He J (2014) Investigation of seismic performance of steel frames based on a quick group search optimizer. Iran Univ Sci Technol 4:27–39
Yuanzheng L, Mengshi L, Qinghua W (2014) Optimal reactive power dispatch with wind power integrated using group search optimizer with intraspecific competition and lévy walk. J Mod Power Syst Clean Energy 2:308–318
Zheng J, Chen J, Wu Q, Jing Z (2015) Reliability constrained unit commitment with combined hydro and thermal generation embedded using self-learning group search optimizer. Energy 81:245–254
Ahmadi A, Kaymanesh A, Heidari A, Agelidis VG (2015) Comment on ‘reliability constrained unit commitment with combined hydro and thermal generation embedded using self-learning group search optimizer by Zheng JH , Chen JJ, Wu QH, Jing ZX [energy 81, (2015) 245–254]. Energy 89: 1103–1105
Xie C, Chen W, Yu W (2015) A hybrid group search optimizer with opposition-based learning and differential evolution. In: International symposium on computational intelligence and intelligent systems, Springer, New York, pp 3–12
Li Y, Zheng X, Xiao X (2015) A study on cooperative multi-objective group search optimizer. In: The 27th Chinese control and decision conference (2015 CCDC), IEEE, pp 3776–3781
Li Y, Zheng X, Lu D (2015) Virtual network embedding based on multi-objective group search optimizer. In: 2015 10th International conference on broadband and wireless computing, communication and applications (BWCCA), IEEE, pp 598–601
Ahmed MM, Elwakil MM, Hassanien AE, Hassanien E (2016) Discrete group search optimizer for community detection in multidimensional social network. In: 12th International computer engineering conference (ICENCO). IEEE 2016, pp 47–52
Lee C-L, Kuo S-C, Lin C-J (2017) An efficient forecasting model based on an improved fuzzy time series and a modified group search optimizer. Appl Intell 46:641–651
Deshmukh RA, Panat A (2017) Interleaver with high dimensional encoding principle using hybrid group search optimizer. In: 2017 International conference on wireless communications, signal processing and networking (WiSPNET), IEEE, pp 2629–2635
Formato RA (2010) Comparative results: group search optimizer and central force optimization, arXiv preprint arXiv:1002.2798
Li L, Zhang W, Xu X, Liu F (2010) An improved group search optimizer algorithm and its application. Spatial Structures 4
He S, Wu Q, Saunders J (2006) A novel group search optimizer inspired by animal behavioural ecology. In: IEEE international conference on evolutionary computation. IEEE 2006, pp 1272–1278
Guanlong D, Shuning Z, Mei Z (2016) A discrete group search optimizer for blocking flow shop multi-objective scheduling. Adv Mech Eng 8:1687814016664262
Cui Z, Gu X (2014) A discrete group search optimizer for hybrid flowshop scheduling problem with random breakdown. Math Probl Eng
Junning C, Wentao H, Dacheng R (2013) An improved algorithm of glowworm swarm optimization based on group search optimizer. J Guilin Univ Electron Technol 16
Wang L-J, Zhong Y-W, Hu X-X (2013) An improved group search optimizer for multi-dimensional function optimization problems. J Chin Comput Syst 34:611–616
Shen H, Zhu Y, Niu B, Wu Q (2009) An improved group search optimizer for mechanical design optimization problems. Prog Nat Sci 19:91–97
Lin C-J, Huang M-L (2019) Efficient hybrid group search optimizer for assembling printed circuit boards. AI EDAM 33:259–274
Xue Z, Chen Z, Ji T, Li M, Wu Q (2019) Estimation of low frequency oscillation parameters using singular value decomposition combined group search optimizer. Electric Power Comp Syst 47:275–287
Li L, Liu F (2011) Group search optimizer and its applications on multi-objective structural optimal design. In: Group search optimization for applications in structural design. Springer, New York, pp 207–246
He S, Wu Q, Saunders J (2006) A group search optimizer for neural network training. In: International conference on computational science and its applications, Springer, New York, pp 934–943
He S, Wu Q, Saunders J (2009) Breast cancer diagnosis using an artificial neural network trained by group search optimizer. Trans Inst Meas Control 31:517–531
Qin G, Liu F, Li L (2009) A quick group search optimizer with passive congregation and its convergence analysis. In: 2009 International conference on computational intelligence and security, volume 1, IEEE, pp 249–253
Xie H, Liu F, Li L (2009) A topology optimization for truss based on improved group search optimizer. In: 2009 International conference on computational intelligence and security, volume 1, IEEE, pp 244–248
Li L-J, Xu X-T, Liu F, Wu Q (2010) The group search optimizer and its application to truss structure design. Adv Struct Eng 13:43–51
Guang Q, Feng L, Lijuan L (2010) A quick group search optimizer and its application to the optimal design of double layer grid shells. In: AIP conference proceedings, volume 1233, American Institute of Physics, pp 718–723
Haobin X, Feng L, Lijuan L, Chun W (2010) Research on topology optimization of truss structures based on the improved group search optimizer. In: AIP conference proceedings, volume 1233, American Institute of Physics, pp 707–712 L
He S (2010) Training artificial neural networks using Lévy group search optimizer. J Multiple-Valued Logic Soft Comput 16
Zhang W-F, Zhu Z-H (2010) Group search optimizer algorithm with predictive model. Inf Technol 6
Shi-Kai Z, Li-Juan L (2010) Application of improved group search optimizer in shape optimization of truss structures. J Guangdong Univ Technol 2
Liu F, Qin G, Li L (2010) A quick group search optimizer and its application research. Eng Mech 27:38–44
Ren F-M, Wang C, Li L-J (2010) A multi-objective group search optimizer and its application in structural optimal design. J Guangxi Univ (Nat Sci Edn) 2
He G, Cui Z, Zeng J (2011) Group search optimizer with interactive dynamic neighborhood. In: International conference on artificial intelligence and computational intelligence, Springer, New York, pp 212–219
Silva DN, Pacifico LD, Ludermir TB (2011) Improved group search optimizer based on cooperation among groups for feedforward networks training with weight decay. In: 2011 IEEE international conference on systems, man, and cybernetics, IEEE, pp 2133–2138
He S, Cooper H, Ward D, Yao X, Heath J (2012) Analysis of premalignant pancreatic cancer mass spectrometry data for biomarker selection using a group search optimizer. Trans Inst Meas Control 34:668–676
Zhan J, Guo C, Wu Q, Wen B (2012) Fast group search optimizer and its application to the economic dispatch of power systems. In: Proceedings of the CSEE S1:
He G-H, Cui Z-H, Tan Y (2012) Interactive dynamic neighborhood differential evolutionary group search optimizer. J Chin Comput Syst 33:809–814
Jin J, Li L, He J, Liu F (2013) Quick group search optimizer applied to the multi-objective optimization of truss structures. Spatial Struct 8
Zhao Z, Yan X, Shi H (2013) Group search optimizer algorithm based on cultural evolution. J East China Univ Sci Technol 39:95–101
Jiang H, Chen F-F, Du W-F (2013) Cooperative cognitive radio spectrum sensing based on improved group search optimizer. J Circuits Syst 1
Balakrishnan R, Karthikeyan T (2019) Microarray gene expression and multiclass cancer classification using extreme learning machine (ELM) with refined group search optimizer (RGSO). Int Sci J Sci Eng Technol 18
Junaed A, Akhand M, Murase K, et al. (2013) Multi-producer group search optimizer for function optimization. In: 2013 international conference on informatics, electronics and vision (ICIEV), IEEE, pp 1–4
Ghosh S, Nandi K, Dar RA (2015) Gbest-guided group search optimizer algorithm
Wang L, Hu X, Ning J, Jing L (2012) A modified group search optimizer algorithm for high dimensional function optimization. In: International conference on information computing and applications, Springer, New York, pp 219–226
Xie Y, Zhao C, Zhang H, Chen D (2014) Degso: hybrid group search optimizer with differential evolution operator. Int J Signal Process Image Process Pattern Recognit 7:285–296
Zhang W-F (2015) Simplified group search optimizer algorithm for large scale global optimization. J Shanghai Jiaotong Univ (Sci) 20:38–43
Wang D, Xiong C, Zhang X (2015) An opposition-based group search optimizer with diversity guidance. Math Problems Eng
Li Y, Wu Q, Li M (2015) Group search optimizer with intraspecific competition and Lévy walk. Knowl-Based Syst 73:44–51
Chen J-J, Ji T, Wu P, Li M (2016) A variant of group search optimizer for global optimization. J Comput Methods Sci Eng 16:219–230
Ravishankkar A, Amudhavalli P (2017) Feature selection using group search optimizer for plant leaf classification. Asian J Inf Technol 16:810–815
Magatrao D, Ghosh S, Valadi J, Siarry P (2013) Simultaneous gene selection and cancer classification using a hybrid group search optimizer. In: Proceedings of the 15th annual conference companion on Genetic and evolutionary computation, pp 7–8
Rafi DM, Bharathi CR (2016) Optimal fuzzy min-max neural network (fmmnn) for medical data classification using modified group search optimizer algorithm. Int J Intell Eng Syst 9:1–10
Zhang W-F, Lu W-K, Luo Y-L (2009) Application of group search optimizer algorithm in optimization of truss structure. Modern Comput 12
Li L, Liu F (2011) Improvements and applications of group search optimizer in structural optimal design. In: Group search optimization for applications in structural design, Springer, New York, pp 97–159
Deng G, Zhang Z, Jiang T, Zhang S (2019) Total flow time minimization in no-wait job shop using a hybrid discrete group search optimizer. Appl Soft Comput 81:105480
Liu H, Wang X, Xiao J, H.-F. WANG (2014) Reactive power optimization based on group search optimizer. Power Syst Protect Control 42:93–99
Moradi-Dalvand M, Mohammadi-Ivatloo B, Najafi A, Rabiee A (2012) Erratum to “continuous quick group search optimizer for solving non-convex economic dispatch problems” [Electr. Power Syst. Res. 93: 93–105]. Electric Power Syst Res 95:275
Reddy AS, Vaisakh K, Vaccaro A (2013) Discussion of “solving non-convex economic dispatch problem with valve point effects using modified group search optimizer method” by Kazem Zare. Electr Power Syst Res 95:353–355
Moradi-Dalvand M, Mohammadi-Ivatloo B, Najafi A, Rabiee A (2012) Continuous quick group search optimizer for solving non-convex economic dispatch problems. Electr Power Syst Res 93:93–105
Guo C, Zhan J, Wu Q (2012) Dynamic economic emission dispatch based on group search optimizer with multiple producers. Electr Power Syst Res 86:8–16
Zare K, Haque MT, Davoodi E (2012) Solving non-convex economic dispatch problem with valve point effects using modified group search optimizer method. Electr Power Syst Res 84:83–89
Reddy AS, Vaisakh K, Vaccaro A (2012) Discussion of “solving non-convex economic dispatch problem with valve point effects using modified group search optimizer method” by Kazem Zare “electric power systems research”. 84: 83–89
Chishti F, Gangwar AK (2014) Group search optimizer for economic load dispatch. Adv Res Electr Electron Eng 1:39–45
Li Y, Li M, Wen B, Wu Q (2014) Power system dispatch with wind power integrated using mean-variance model and group search optimizer. In: IEEE PES general meeting|conference and exposition. IEEE pp 1–5
Wen-Fen Z (2014) Improved group search optimizer algorithm for design optimization of structures. Comput Knowl Technol 2014:64
Li L, Liu F (2011) Optimum design of structures with group search optimizer algorithm. In: Group search optimization for applications in structural design, Springer, New York, pp 69–96
Li P, Jiang H, Sun Q, Zhou J (2010) Distribution network reconfiguration based on group search optimizer. Power Syst Technol 12
Feng X, Ma M, Yu H, Wang Z (2015) Social group search optimizer algorithm for ad hoc network. Adhoc and Sensor Wireless Netw 28
Nezhadnaeini MF, Hajivand M, Abasi M, Mohajeryami S (2016) Optimal allocation of distributed generation units based on two different objectives by a novel version group search optimizer algorithm in unbalanced loads system. Revue Roumaine des Sci Tech 61:338–342
Krishnaprabha R, Aloor G (2014) Group search optimizer algorithm in wireless sensor network localization. In: 2014 International conference on advances in computing, communications and informatics (ICACCI), IEEE, pp 1953–1957
Feng X, Liu X, Yu H (2016) A new internet of things group search optimizer. Int J Commun Syst 29:535–552
Su HS, An XW (2014) An, Power distribution network planning based on group search optimizer algorithm. In: Advanced materials research, volume 971, Trans Tech Publ, pp 1284–1287
Wang D, Xiong C, Huang W (2014) Group search optimizer for the mobile location management problem. The Sci World J
Kang Q, Lan T, Yan Y, Wang L, Wu Q (2012) Group search optimizer based optimal location and capacity of distributed generations. Neurocomputing 78:55–63
Harikrishnan R, Kumar VJS (2015) An integrated Xbee arduino with group search optimizer approach for localization in wireless sensor networks. Indian J Sci Technol 8:1
Mary AA, Chitra K (2019) Ogso-dr: oppositional group search optimizer based efficient disaster recovery in a cloud environment. J Ambient Intell Humaniz Comput 10:1885–1895
Zhou Y-X, Li C-B, He Y-Q, Liu Y, Li L, Cao Y-J (2012) Location and penetration of distributed generation based on group search optimizer. In: Proceedings of the Chinese society of universities for electric power system and its automation 5
Luo L, Xie J, Zhou H, Liang T, Feng S-J, Qing D-L (2012) A novel realization algorithm of group search optimizer. J Nantong Univ (Nat Sci Edn) 2
Gharehchopogh FS, Gholizadeh H (2019) A comprehensive survey: whale optimization algorithm and its applications. Swarm Evolut Comput 48:1–24
Malhotra R, Khanna M, Raje RR (2017) On the application of search-based techniques for software engineering predictive modeling: a systematic review and future directions. Swarm Evolut Comput 32:85–109
Rakshit P, Konar A, Das S (2017) Noisy evolutionary optimization algorithms-a comprehensive survey. Swarm Evolut Comput 33:18–45
Gotmare A, Bhattacharjee SS, Patidar R, George NV (2017) Swarm and evolutionary computing algorithms for system identification and filter design: a comprehensive review. Swarm Evolut Comput 32:68–84
Saremi S, Mirjalili S, Lewis A (2017) Grasshopper optimisation algorithm: theory and application. Adv Eng Softw 105:30–47
Eberhart R, Kennedy J (1995) A new optimizer using particle swarm theory. In: MHS’95 Proceedings of the sixth international symposium on micro machine and human science, IEEE, pp 39–43
Abualigah LMQ, Hanandeh ES (2015) Applying genetic algorithms to information retrieval using vector space model. Int J Comput Sci Eng Appl 5:19
Yang X-S (2010) A new metaheuristic bat-inspired algorithm. In: Nature inspired cooperative strategies for optimization (NICSO 2010), Springer, pp 65–74
Yang X-S (2010) Firefly algorithm, stochastic test functions and design optimisation. arXiv preprint arXiv:1003.1409
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The author declares that he has no conflict of interest.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
This article has been retracted. Please see the retraction notice for more detail: https://doi.org/10.1007/s00521-024-10103-7
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Abualigah, L. RETRACTED ARTICLE: Group search optimizer: a nature-inspired meta-heuristic optimization algorithm with its results, variants, and applications. Neural Comput & Applic 33, 2949–2972 (2021). https://doi.org/10.1007/s00521-020-05107-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00521-020-05107-y