{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T08:12:23Z","timestamp":1777363943546,"version":"3.51.4"},"reference-count":57,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2013,3,26]],"date-time":"2013-03-26T00:00:00Z","timestamp":1364256000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Memetic Comp."],"published-print":{"date-parts":[[2013,9]]},"DOI":"10.1007\/s12293-013-0111-9","type":"journal-article","created":{"date-parts":[[2013,3,25]],"date-time":"2013-03-25T06:42:03Z","timestamp":1364193723000},"page":"229-251","source":"Crossref","is-referenced-by-count":91,"title":["Novel inertia weight strategies for particle swarm optimization"],"prefix":"10.1007","volume":"5","author":[{"given":"Pinkey","family":"Chauhan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kusum","family":"Deep","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Millie","family":"Pant","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2013,3,26]]},"reference":[{"key":"111_CR1","doi-asserted-by":"crossref","first-page":"541","DOI":"10.1016\/S1874-1029(11)60205-X","volume":"37","author":"A Alireza","year":"2011","unstructured":"Alireza A (2011) PSO with adaptive mutation and inertia weight and its application in parameter estimation of dynamic systems. Acta Automatica Sinica 37:541\u2013549","journal-title":"Acta Automatica Sinica"},{"key":"111_CR2","doi-asserted-by":"crossref","unstructured":"Arumugam MS, Rao, MCV (2006) On the performance of the particle swarm optimization algorithm with various inertia weight variants for computing optimal control of a class of hybrid systems. Int J Discrete Dyn Nat Soc pp 1\u201317","DOI":"10.1155\/DDNS\/2006\/79295"},{"key":"111_CR3","doi-asserted-by":"crossref","unstructured":"Bansal JC, Singh PK, Saraswat M, Verma A, Jadon SS, Abraham A (2011) Inertia weight strategies in particle swarm optimization. In: Proceedings of third world congress on nature and biologically inspired computing (NaBIC-2011), pp 633\u2013640","DOI":"10.1109\/NaBIC.2011.6089659"},{"key":"111_CR4","doi-asserted-by":"crossref","unstructured":"Chatterjee A, Siarry P (2006) Nonlinear Inertia weight variation for dynamic adaption in Particle swarm optimization. In: Computers and operation research, vol 33, Elsevier, Amsterdam, pp 859\u2013871","DOI":"10.1016\/j.cor.2004.08.012"},{"key":"111_CR5","doi-asserted-by":"crossref","unstructured":"Chen G, Huang X, Jia J, Min Z (2006) Natural exponential Inertia weight strategy in particle swarm optimization. In: Proceedings of 6th world congress on intelligent control, pp 3672\u20133675","DOI":"10.1109\/WCICA.2006.1713055"},{"key":"111_CR6","unstructured":"Chen JY, Shen JJ (2012) Structure learning of Bayesian Network using a Chaos-based PSO. Adv Mater Res pp 2292\u20132295"},{"key":"111_CR7","first-page":"1951","volume":"3","author":"M Clerc","year":"1999","unstructured":"Clerc M (1999) The swarm and the queen: towards a deterministic and adaptive particle swarm optimization. Proc IEEE Congr Evol Comput 3:1951\u20131957","journal-title":"Proc IEEE Congr Evol Comput"},{"key":"111_CR8","unstructured":"Clerc M (2001) Think locally, act locally: the way of life of cheap-PSO. An Adaptive PSO, Technical report, http:\/\/clerc.maurice.free.fr\/pso\/"},{"issue":"7","key":"111_CR9","doi-asserted-by":"crossref","first-page":"1315","DOI":"10.1016\/j.ijepes.2011.06.007","volume":"33","author":"PK Dash","year":"2011","unstructured":"Dash PK, Mallick RK (2011) Accurate tracking of harmonic signals in VSC-HVDC systems using PSO based unscented transformation. Int J Elec Power Energy Syst 33(7):1315\u20131325","journal-title":"Int J Elec Power Energy Syst"},{"key":"111_CR10","doi-asserted-by":"crossref","unstructured":"Deep K, Arya M, Bansal JC (2011) A non-deterministic adaptive inertia weight in PSO. In: Proceedings of 13th annual conference on genetic and evolutionary computation (GECCO-2011). ACM, New York, pp 1155\u20131162","DOI":"10.1145\/2001576.2001732"},{"key":"111_CR11","first-page":"1","volume":"7","author":"J Demsar","year":"2006","unstructured":"Demsar J (2006) Statiscally comparisons of classifier over multiple date set. J Mach Learn Res 7:1\u201330","journal-title":"J Mach Learn Res"},{"issue":"1","key":"111_CR12","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/j.swevo.2011.02.002","volume":"1","author":"J Derrac","year":"2011","unstructured":"Derrac J, Garc\u00eda SR, Molina D, Herrera F (2011) A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms. Swarm Evol Comput 1(1):3\u201318","journal-title":"Swarm Evol Comput"},{"key":"111_CR13","doi-asserted-by":"crossref","unstructured":"Dong C, Wang G, Chen Z (2008a) The inertia weight self-adapting in PSO. In: Proceedings of 7th world congress on intelligent control and automation (WCICA-2008), pp 5313\u20135316","DOI":"10.1109\/WCICA.2008.4593794"},{"key":"111_CR14","first-page":"1195","volume":"1","author":"C Dong","year":"2008","unstructured":"Dong C, Wang G, Chen Z, Yu Z (2008b) A method of self-adaptive inertia weight for PSO. CSSE 1:1195\u20131198","journal-title":"CSSE"},{"key":"111_CR15","first-page":"84","volume":"1","author":"RC Eberhart","year":"2000","unstructured":"Eberhart RC, Shi Y (2000) Comparing inertia weights and constriction factors in particle swarm optimization. Proc IEEE Congr Evol Comput 1:84\u201388","journal-title":"Proc IEEE Congr Evol Comput"},{"key":"111_CR16","doi-asserted-by":"crossref","unstructured":"Ememipour J, Nejad MMS, Ebadzadeh MM, Rezanejad J (2009) Introduce a new inertia weight for particle swarm optimization. In: Proceedings of fourth international conference on computer sciences and convergence information technology (ICCIT-2009). pp 1650\u20131653","DOI":"10.1109\/ICCIT.2009.297"},{"key":"111_CR17","doi-asserted-by":"crossref","first-page":"1493","DOI":"10.1016\/j.phpro.2012.02.221","volume":"24","author":"C Fei","year":"2012","unstructured":"Fei C, Ding F, Zhao X (2012) Network partition of switched industrial ethernet by using novel particle swarm optimization. Physics Procedia Part B 24:1493\u20131499","journal-title":"Physics Procedia Part B"},{"key":"111_CR18","doi-asserted-by":"crossref","unstructured":"Feng CS, Cong S, Feng XY (2007a) A new adaptive inertia weight strategy in particle swarm optimization. In: Proceedings of IEEE congress on evolutionary computation, (CEC-2007). pp 4186\u20134190","DOI":"10.1109\/CEC.2007.4425017"},{"key":"111_CR19","doi-asserted-by":"crossref","unstructured":"Feng Y, Teng G, Wang A, Yao YM (2007b) Chaotic inertia weight in particle swarm optimization. In: Proceedings of second international conference on innovative computing, information and control (ICICIC-2007), pp 475\u2013478","DOI":"10.1109\/ICICIC.2007.209"},{"key":"111_CR20","doi-asserted-by":"crossref","unstructured":"Feng Y, Yao YM, Wang A (2007c) Comparing with chaotic inertia weights in particle swarm optimization. In: Proceedings of international conference on machine learning and cybernetics, pp 329\u2013333","DOI":"10.1109\/ICMLC.2007.4370164"},{"key":"111_CR21","first-page":"208","volume":"3\u20134","author":"I Ghali","year":"2009","unstructured":"Ghali I, El-Dessouki N, Mervat AN, Bakrawi L (2009) Exponential particle swarm optimization approach for improving data clustering. Int J Electr Electron Eng 3\u20134:208\u2013212","journal-title":"Int J Electr Electron Eng"},{"key":"111_CR22","doi-asserted-by":"crossref","unstructured":"Hashim SZM, Permana KE (2009) Fitting membership function with PSO inertia weight for truck backer-upper problem. In: Proceedings Third Asia international conference on modelling and simulation. pp 25\u201328","DOI":"10.1109\/AMS.2009.131"},{"key":"111_CR23","unstructured":"Hu JZ, Xu J, Wang JQ, Xu T (2009) Research on particle swarm optimization with dynamic inertia weight. In: Proceedings Iiternational conference on management and service science, China, pp 1\u20134"},{"key":"111_CR24","unstructured":"JianXin W, WenZHi L, WeiGuo Z, Qiang L (2008) Exponential type adaptive inertia weighted particle swarm optimization algorithm. In: Proceedings of 2nd international conference on genetic and evolutionary computing, (WGEC-2008). IEEE Computer Society, pp 79\u201382"},{"key":"111_CR25","doi-asserted-by":"crossref","first-page":"698","DOI":"10.1016\/j.chaos.2006.09.063","volume":"37","author":"B Jiao","year":"2008","unstructured":"Jiao B, Lian Z, Gu X (2008) A dynamic inertia weight particle swarm optimization algorithm. Chaos Solitons Fractals 37:698\u2013705","journal-title":"Chaos Solitons Fractals"},{"key":"111_CR26","doi-asserted-by":"crossref","unstructured":"Kennedy J, Mendes R (2002) Population structure and particle performance. In: Proceedings IEEE congress on evolutionary computation, pp 1671\u20131676","DOI":"10.1109\/CEC.2002.1004493"},{"key":"111_CR27","first-page":"1931","volume":"3","author":"J Kennedy","year":"1999","unstructured":"Kennedy J (1999) Small worlds and mega-minds: effects of neighborhood topology on particle swarm performance. Proc IEEE Congr Evol Comput 3:1931\u20131938","journal-title":"Proc IEEE Congr Evol Comput"},{"key":"111_CR28","doi-asserted-by":"crossref","unstructured":"Kennedy J, Eberhart RC (1995) Particle swarm optimization. In: Proceedings IEEE international joint conference on neural networks, pp 1942\u20131948","DOI":"10.1109\/ICNN.1995.488968"},{"key":"111_CR29","doi-asserted-by":"crossref","unstructured":"Kumar P, Pant M (2012) Enhanced mutation strategy for differential evolution. In: IEEE Congress on Evolutionary Computation (CEC), pp 1\u20136, 10\u201315","DOI":"10.1109\/CEC.2012.6252914"},{"key":"111_CR30","doi-asserted-by":"crossref","unstructured":"Li R, Gao YL (2009) Particle swarm optimization algorithm with exponent decreasing inertia weight and stochastic mutation. In: Proceedings of second international conference on information and computing science, vol 1, pp 66\u201369","DOI":"10.1109\/ICIC.2009.24"},{"key":"111_CR31","doi-asserted-by":"crossref","unstructured":"Liu C, Ouyang C, Zhu P, Tang W, (2010) An adaptive fuzzy weight PSO algorithm. In: Proceedings of fourth international conference on genetic and evolutionary computing, pp 8\u201310","DOI":"10.1109\/ICGEC.2010.10"},{"issue":"6","key":"111_CR32","first-page":"70","volume":"27","author":"W Miaomiao","year":"2010","unstructured":"Miaomiao W, Yuelin G (2010) A new particle swarm optimization with dynamically adaptive inertia weight and hybrid mutation. Comput Appl Softw 27(6):70\u201372","journal-title":"Comput Appl Softw"},{"key":"111_CR33","doi-asserted-by":"crossref","first-page":"3658","DOI":"10.1016\/j.asoc.2011.01.037","volume":"11","author":"A Nickabadi","year":"2011","unstructured":"Nickabadi A, Ebadzadeh MM, Safabakhsh R (2011) A novel particle swarm optimization with adaptive inertia weight. Appl Soft Comput 11:3658\u20133670","journal-title":"Appl Soft Comput"},{"key":"111_CR34","doi-asserted-by":"crossref","unstructured":"Pant M, Thangraj R, Singh VP (2007) Particle swarm optimization using Gaussian inertia weight. In: Proceedings of international conference on computational intelligence and multimedia applications, vol 1, pp 97\u2013102","DOI":"10.1109\/ICCIMA.2007.96"},{"key":"111_CR35","doi-asserted-by":"crossref","unstructured":"Peer ES, Van den Bergh F, Engelbrecht AP (2003) Using neighborhoods with the guaranteed convergence PSO. In: Proceedings of IEEE swarm intelligence symposium, pp 235\u2013242","DOI":"10.1109\/SIS.2003.1202274"},{"key":"111_CR36","doi-asserted-by":"crossref","unstructured":"Peram T, Veeramachaneni K, Mohan CK (2003) Fitness-distance-ratio based particle swarm optimization. In: Proceedings of IEEE swarm intelligence symposium, pp 174\u2013181","DOI":"10.1109\/SIS.2003.1202264"},{"key":"111_CR37","unstructured":"Ratnaweera A, Halgamuge S, Watson H (2003) Particle swarm optimization with self-adaptive acceleration coefficients. In: Proceedings of first international conference on fuzzy systems and knowledge discovery, pp 264\u2013268"},{"key":"111_CR38","doi-asserted-by":"crossref","unstructured":"Shi Y, Eberhart RC (1999) Empirical study of particle swarm optimization. In: Proceedings of the congress on evolutionary computation (CEC-1999), vol 3, pp 1945\u20131950","DOI":"10.1109\/CEC.1999.785511"},{"key":"111_CR39","first-page":"101","volume":"1","author":"Y Shi","year":"2001","unstructured":"Shi Y, Eberhart RC (2001) Fuzzy adaptive particle swarm optimization. Proc IEEE Congr Evol Comput 1:101\u2013106","journal-title":"Proc IEEE Congr Evol Comput"},{"key":"111_CR40","doi-asserted-by":"crossref","unstructured":"Shi Y, Eberhart RC (1998) Parameter selection in particle swarm optimization. In: Proceedings of seventh annual conference on evolutionary programming, pp 591\u2013600","DOI":"10.1007\/BFb0040810"},{"key":"111_CR41","unstructured":"Suganthan PN (1999) Particle swarm optimiser with neighborhood operator. In: Proceedings of IEEE congress on evolutionary computation, pp 1958\u20131962"},{"key":"111_CR42","first-page":"4068","volume":"31","author":"X Sun","year":"2010","unstructured":"Sun X, Zhou DW, Zhang XW (2010) Convergence analysis and parameter selection of PSO model with inertia weight. Comput Eng Design 31:4068\u20134071","journal-title":"Comput Eng Design"},{"key":"111_CR43","doi-asserted-by":"crossref","unstructured":"Suresh K, Ghosh S, Kundu D, Sen A, Das S, Abraham A (2008) Inertia-adaptive particle swarm optimizer for improved global search. In: Proceedings of eighth international conference on intelligent systems design and applications (ISDA-2008), vol 2, pp 253\u2013258","DOI":"10.1109\/ISDA.2008.199"},{"issue":"6","key":"111_CR44","doi-asserted-by":"crossref","first-page":"317","DOI":"10.1016\/S0020-0190(02)00447-7","volume":"85","author":"IC Trelea","year":"2003","unstructured":"Trelea IC (2003) The particle swarm optimization algorithm: convergence analysis and parameter selection. Inf Process Lett 85(6):317\u2013325","journal-title":"Inf Process Lett"},{"issue":"17","key":"111_CR45","first-page":"32","volume":"40","author":"SM Uma","year":"2012","unstructured":"Uma SM, Gandhi RK, Kirubakaran E (2012) A hybrid PSO with dynamic inertia weight and GA approach for discovering classification rule in data mining. Int J Comput Appl 40(17):32\u201337","journal-title":"Int J Comput Appl"},{"key":"111_CR46","doi-asserted-by":"crossref","unstructured":"Umapathy P, Venkataseshaiah C, Arumugam MS (2010) Particle swarm optimization with various inertia weight variants for optimal power flow solution. Discrete Dyn Nat Soc pp 1\u201315","DOI":"10.1155\/2010\/462145"},{"key":"111_CR47","doi-asserted-by":"crossref","unstructured":"Venter G, Sobieszczanski-Sobieski J (2003) Particle swarm optimization. J Am Inst Aeronaut Astronaut 41(8):1583\u20131589","DOI":"10.2514\/2.2111"},{"key":"111_CR48","doi-asserted-by":"crossref","unstructured":"Wang W, Qiu L (2010) Optimal reservoir operation using PSO with adaptive random inertia weight. In: Proceedings of international conference on artificial intelligence and computational intelligence, vol 3, pp 377\u2013381. doi: 10.1109\/AICI.2010.316","DOI":"10.1109\/AICI.2010.316"},{"key":"111_CR49","unstructured":"Wang XLQ, Liu H, Li L (2009) Particle swarm optimization with dynamic inertia weight and mutation. In: Proceedings of third international conference on genetic and evolutionary computing, China, pp 620\u2013623"},{"key":"111_CR50","doi-asserted-by":"crossref","first-page":"3484","DOI":"10.4028\/www.scientific.net\/AMR.97-101.3484","volume":"97\u2013101","author":"XL Wang","year":"2010","unstructured":"Wang XL, Yang Y, Zeng Q, Wang JQ (2010) Particle swarm optimization with adaptive inertia weight and its application in optimization design. Adv Mater Res 97\u2013101:3484\u20133488","journal-title":"Adv Mater Res"},{"key":"111_CR51","unstructured":"Xin WJ, Zhi LW, Guo ZW, Qiang L (2008) Exponential type adaptive inertia weighted particle swarm optimization algorithm. In: Proceedings of second international conference on genetic and evolutionary computing, pp 79\u201382"},{"key":"111_CR52","doi-asserted-by":"crossref","unstructured":"Yang H, Cheng YH, Chuang LY (2010) A novel chaotic inertia weight particle swarm optimization for PCR primer design. In: Proceedings of international conference on technologies and applications of artificial intelligence, pp 373\u2013378","DOI":"10.1109\/TAAI.2010.66"},{"key":"111_CR53","first-page":"1205","volume":"189","author":"X Yang","year":"2007","unstructured":"Yang X, Yuan J, Mao H (2007) A modified particle swarm optimizer with dynamic adaption. Appl MathComput 189:1205\u20131213","journal-title":"Appl MathComput"},{"key":"111_CR54","doi-asserted-by":"crossref","unstructured":"Yoshida H, Fukuyama Y, Takayama S, Nakanishi Y (1999) A particle swarm optimization for reactive power and voltage control in electric power systems considering voltage security assessment. In: Proceedings of IEEE international conference on systems, man, and cybernetics, vol 6, pp 497\u2013502","DOI":"10.1109\/ICSMC.1999.816602"},{"key":"111_CR55","unstructured":"Zheng Q, Fan Y, Zhewen S, Yu W (2006) Adaptive inertia weight particle swarm optimization, Artificial Intelligence and Soft Computing (ICAISC-2006). In: Lecture notes in computer science, vol 4029. Springer, Berlin, pp 450\u2013459"},{"key":"111_CR56","unstructured":"Zhou Z, Shi Y (2011) Inertia weight adaption in particle swarm optimization algorithm. Advances in swarm intelligence. In: Lecture notes in computer science, vol 6728, pp 71\u201379"},{"key":"111_CR57","doi-asserted-by":"crossref","unstructured":"Zhu H, Zheng C, Hu X, Li X (2008) Adaptive PSO using random inertia weight and its application in UAV path planning. In: Proceedings of seventh international symposium on instrumentation and control technology: measurement theory and systems and aeronautical equipment (SPIE), vol 7128, pp 1\u20135","DOI":"10.1117\/12.806636"}],"container-title":["Memetic Computing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s12293-013-0111-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s12293-013-0111-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s12293-013-0111-9","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,7,11]],"date-time":"2019-07-11T09:20:11Z","timestamp":1562836811000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s12293-013-0111-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,3,26]]},"references-count":57,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2013,9]]}},"alternative-id":["111"],"URL":"https:\/\/doi.org\/10.1007\/s12293-013-0111-9","relation":{},"ISSN":["1865-9284","1865-9292"],"issn-type":[{"value":"1865-9284","type":"print"},{"value":"1865-9292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2013,3,26]]}}}