Abstract
Algorithms inspired by the intelligent social behavior of simple agents have become popular among the researchers in the recent years. These algorithms are able to find the solution of those real-world optimization problems, which otherwise cannot be solved easily by deterministic techniques. Spider Monkey Optimization (SMO) is one such algorithm which is inspired by the intelligent behavior of spider monkeys. SMO and its variants have been successful and effective in dealing with complex real world optimization problems due to its high efficacy. This paper presents an intense review of SMO, its variants, applications and relative performance with other algorithms .
Similar content being viewed by others
References
Agarwal N, Jain SC (2017) Fast convergent spider monkey optimization algorithm. In: Proceedings of sixth international conference on soft computing for problem solving, Springer, Singapore, pp 42–51
Agrawal A, Farswan P, Agrawal V, Tiwari DC, Bansal JC (2017) On the hybridization of spider monkey optimization and genetic algorithms. In: Proceedings of sixth international conference on soft computing for problem solving, Springer, Singapore, pp 185–196
Al-Azza AA, Al-Jodah AA, Harackiewicz FJ (2016a) Spider monkey optimization: a novel technique for antenna optimization. IEEE Antennas Wirel Propag Lett 15:1016–1019
Al-Azza AA, Al-Jodah AA, Harackiewicz FJ (2016) Spider monkey optimization (SMO): a novel optimization technique in electromagnetics. In: Radio and wireless symposium (RWS), 2016 IEEE, pp 238–240. IEEE
Ali AF (2017) An improved spider monkey optimization for solving a convex economic dispatch problem. In: Nature-inspired computing and optimization, Springer, pp 425–448
Arora V, Sood P, Keshari KU (2015) A comparison of HPSOWM, krill herd and Spider Monkey optimization algorithms. In: 2015 2nd International conference on recent advances in engineering & computational sciences (RAECS), pp 1–5. IEEE
Bansal JC, Sharma H, Jadon SS, Clerc M (2014) Spider monkey optimization algorithm for numerical optimization. Memet Comput 6(1):31–47
Bonabeau E, Dorigo M, Theraulaz G (1999) Swarm intelligence: from natural to artificial systems, vol 1. Oxford University Press, Oxford
Cheruku R, Edla DR, Kuppili V (2017) SM-RuleMiner: Spider monkey based rule miner using novel fitness function for diabetes classification. Comput Biol Med 81:79–92
De Castro LN, Von Zuben FJ (1999) Artificial immune systems: part I—basic theory and applications. Universidade Estadual de Campinas, Dezembro de, Tech. Rep, 210(1)
Dorigo M, Birattari M, Stutzle T (2006) Ant colony optimization. IEEE Comput Intell Mag 1(4):28–39
Eberhart R, Kennedy J (1995) A new optimizer using particle swarm theory. In: Proceedings of the sixth international symposium on micro machine and human science, 1995. MHS’95, pp 39–43. IEEE
Formato RA (2008). Central force optimization: a new nature inspired computational framework for multidimensional search and optimization. In: Nature inspired cooperative strategies for optimization (NICSO 2007), Springer, Berlin, pp 221–238
Gui T, Ma C, Wang F, Li J, Wilkins DE (2016) A novel cluster-based routing protocol wireless sensor networks using Spider Monkey Optimization. In: 42nd Annual conference of the IEEE industrial electronics society, IECON 2016, pp 5657–5662. IEEE
Gupta K, Deep K (2016a) Investigation of suitable perturbation rate scheme for spider monkey optimization algorithm. In: Proceedings of fifth international conference on soft computing for problem solving, Springer, Singapore, pp 839–850
Gupta K, Deep K (2016b) Tournament selection based probability scheme in spider monkey optimization algorithm. In: Harmony search algorithm, Springer, Berlin, pp 239–250
Gupta K, Deep K, Bansal JC (2017a) Spider monkey optimization algorithm for constrained optimization problems. Soft Comput 21(23):6933–6962
Gupta K, Deep K, Bansal JC (2017b) Improving the local search ability of spider monkey optimization algorithm using quadratic approximation for unconstrained optimization. Comput Intell 33(2):210–240
Hazrati G, Sharma, H, Sharma N (2016) Adaptive step-size based spider monkey optimization. In Power electronics, intelligent control and energy systems (ICPEICES), international conference on IEEE, pp 1–5
Hazrati G, Sharma H, Sharma N, Bansal JC (2016) Modified spider monkey optimization. In: International workshop on computational intelligence (IWCI), IEEE, pp 209–214
Jeanne RL (1986) The evolution of the organization of work in social insects. Monitore Zoologico Italiano (Ital J Zool) 20(2):119–133
Kaur A (2016) Comparison analysis of CDMA multiuser detection using PSO and SMO. Int J Comput Appl 133(2):47–50
Kim SS, Kim IH, Mani V, Kim HJ (2008) Ant colony optimization for SONET ring loading problem. Int J Innovative Comput Inf Control 4(7):1617–1626
Krishnanand KN, Amruth P, Guruprasad MH, Bidargaddi SV, Ghose D (2006) Glowworm-inspired robot swarm for simultaneous taxis towards multiple radiation sources. In: Proceedings 2006 IEEE international conference on robotics and automation, 2006. ICRA 2006, pp 958–963. IEEE
Kumar S, Kumari R (2014) Modified position update in spider monkey optimization algorithm. In: International Journal of Emerging Technologies in Computational and Applied Sciences (IJETCAS
Kumar S, Kumar Sharma V, Kumari R (2014) Self-adaptive spider monkey optimization algorithm for engineering optimization problems. Int J Inf Commun Comput Technol II:96–107
Kumar S, Kumari R, Sharma VK (2015) Fitness based position update in spider monkey optimization algorithm. Procedia Comput Sci 62:442–449
Lenin K, Reddy BR, Kalavathi MS (2015) Modified monkey optimization algorithm for solving optimal reactive power dispatch problem. Indones J Electr Eng Inf (IJEEI) 3(2):55–62
Mittal N, Singh U, Salgotra R, Sohi BS A (2017) boolean spider monkey optimization based energy efficient clustering approach for WSNs. Wirel Networks. https://doi.org/10.1007/s11276-017-1459-4
Nagar AK, Robinson T (2012) Recent advances in bio-inspired computing: theory and applications J. UCS Special Issue. J Univ Comput Sci 18(13):1757–1759
Nayak N, Mahali MS, Majumder I, Jena RK (2016) Dynamic stability improvement of VSC-HVDC connected multi machine power system by Spider Monkey Optimization based PI controller. In: International conference on electrical, electronics, and optimization techniques (ICEEOT), pp. 152–157. IEEE
Oster GF, Wilson EO (1978) Caste and ecology in the social insects. Princeton University Press, Princeton
Pal SS, Kumar S, Kashyap M, Choudhary Y, Bhattacharya M (2016) Multi-level thresholding segmentation approach based on spider monkey optimization algorithm. In: Proceedings of the second international conference on computer and communication technologies, Springer India, pp 273–287
Price K, Storn RM, Lampinen JA (2006) Differential evolution: a practical approach to global optimization. Springer, Berlin
Rajan A, Malakar T (2016) Optimum economic and emission dispatch using exchange market algorithm. Int J Electr Power Energy Syst 82:545–560
Ram DJ, Sreenivas TH, Subramaniam KG (1996) Parallel simulated annealing algorithms. J Parallel Distrib Comput 37(2):207–212
Rao VSV, Shekhawat RS, Srivastava VK (2012) A reliable digital image watermarking scheme based on SVD and particle swarm optimization. In: 2012 Students conference on engineering and systems (SCES), pp 1–6. IEEE
Sangwan V, Sharma A, Kumar R, Rathore AK (2016). Estimation of battery parameters of the equivalent circuit models using meta-heuristic techniques. In: IEEE International conference on power electronics, intelligent control and energy systems (ICPEICES), pp 1–6. IEEE
Satsangi S, Gulati A, Kalra PK, Patvardhan C (2012) Application of genetic algorithms for evolution of quantum equivalents of boolean circuits. Int J Electr Comput Electr Commun Eng 6(3):275–279
Selvam K, Kumar DV (2017) Frequency control of micro grid with wind perturbations using levy walks with spider monkey optimization algorithm. Int J Renew Energy Res (IJRER) 7(1):146–156
Sharma H, Bansal JC, Arya KV (2014) Self balanced differential evolution. J Comput Sci 5(2):312–323
Sharma A, Sharma A, Panigrahi BK, Kiran D, Kumar R (2016a) Ageist spider monkey optimization algorithm. Swarm Evol Comput 28:58–77
Sharma A, Sharma H, Bhargava A, Sharma N, Bansal JC (2016b) Optimal placement and sizing of capacitor using Limaçon inspired spider monkey optimization algorithm. Memetic Comput. https://doi.org/10.1007/s12293-016-0208-z
Sharma A, Sharma H, Bhargava A, Sharma N (2016c) Optimal design of PIDA controller for induction motor using Spider Monkey Optimization algorithm. Int J Metaheuristics 5(3–4):278–290
Sharma A, Sharma H, Bhargava A, Sharma N, Bansal JC (2016d) Optimal power flow analysis using Lévy flight spider monkey optimisation algorithm. Int J Artif Intell Soft Comput 5(4):320–352
Sharma A, Sharma H, Bhargava A, Sharma N (2017) Power law-based local search in spider monkey optimisation for lower order system modelling. Int J Syst Sci 48(1):150–160
Singh U, Salgotra R (2016) Optimal synthesis of linear antenna arrays using modified spider monkey optimization. Arab J Sci Eng 41(8):2957–2973
Singh U, Salgotra R, Rattan M (2016) A novel binary spider monkey optimization algorithm for thinning of concentric circular antenna arrays. IETE J Res 62(6):736–744
Sivalingam R, Chinnamuthu S (2017) A hybrid self-adaptive spider monkey optimization for automatic generation control. Int J Comput Technol Appl 10(03):237–244
Venkata Rao R (2007) Vendor selection in a supply chain using analytic hierarchy process and genetic algorithm methods. Int J Serv Oper Manag 3(3):355–369
Vesterstrom J, Thomsen R (2004) A comparative study of differential evolution, particle swarm optimization, and evolutionary algorithms on numerical benchmark problems. In: Congress on evolutionary computation, 2004, CEC2004, vol 2, pp 1980–1987. IEEE
Vinod G, Kushwaha HS, Verma AK, Srividya A (2004) Optimisation of ISI interval using genetic algorithms for risk informed in-service inspection. Reliab Eng Syst Saf 86(3):307–316
Wu H, Yan Y, Liu C, Zhang J (2016) Pattern synthesis of sparse linear arrays using spider monkey optimization. IEICE Trans Commun. https://doi.org/10.1587/transcom.2016EBP3203
Yang XS, Gandomi AH, Talatahari S, Alavi AH (eds) (2012) Metaheuristics in water, geotechnical and transport engineering. Newnes, Oxford
Yang XS, Cui Z, Xiao R, Gandomi AH, Karamanoglu M (eds) (2013) Swarm intelligence and bio-inspired computation: theory and applications. Newnes, Oxford
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Agrawal, V., Rastogi, R. & Tiwari, D.C. Spider Monkey Optimization: a survey. Int J Syst Assur Eng Manag 9, 929–941 (2018). https://doi.org/10.1007/s13198-017-0685-6
Received:
Revised:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13198-017-0685-6