{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,5]],"date-time":"2026-05-05T15:53:37Z","timestamp":1777996417984,"version":"3.51.4"},"reference-count":60,"publisher":"Springer Science and Business Media LLC","issue":"21-22","license":[{"start":{"date-parts":[[2024,11,1]],"date-time":"2024-11-01T00:00:00Z","timestamp":1730419200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,11,1]],"date-time":"2024-11-01T00:00:00Z","timestamp":1730419200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Soft Comput"],"published-print":{"date-parts":[[2024,11]]},"DOI":"10.1007\/s00500-024-10314-z","type":"journal-article","created":{"date-parts":[[2024,11,25]],"date-time":"2024-11-25T03:55:35Z","timestamp":1732506935000},"page":"12835-12868","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Multi-objective optimal power flow problem using Nelder\u2013Mead based Prairie Dog optimization algorithm"],"prefix":"10.1007","volume":"28","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7353-6381","authenticated-orcid":false,"given":"Bimal Kumar","family":"Dora","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sunil","family":"Bhat","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sudip","family":"Halder","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ishan","family":"Srivastava","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,11,25]]},"reference":[{"key":"10314_CR1","doi-asserted-by":"crossref","first-page":"4027","DOI":"10.1007\/s00500-020-05431-4","volume":"25","author":"S Abd El-sattar","year":"2021","unstructured":"Abd El-sattar S, Kamel S, Ebeed M, Jurado F (2021) An improved version of salp swarm algorithm for solving optimal power flow problem. Soft Comput 25:4027\u20134052","journal-title":"Soft Comput"},{"issue":"2","key":"10314_CR3","doi-asserted-by":"crossref","first-page":"2845","DOI":"10.1016\/j.asoc.2010.11.014","volume":"11","author":"M Basu","year":"2011","unstructured":"Basu M (2011) Economic environmental dispatch using multi-objective differential evolution. Appl Soft Comput 11(2):2845\u20132853","journal-title":"Appl Soft Comput"},{"key":"10314_CR4","doi-asserted-by":"crossref","first-page":"2999","DOI":"10.1007\/s00500-019-04077-1","volume":"24","author":"PP Biswas","year":"2020","unstructured":"Biswas PP, Suganthan PN, Mallipeddi R, Amaratunga GA (2020) Multi-objective optimal power flow solutions using a constraint handling technique of evolutionary algorithms. Soft Comput 24:2999\u20133023","journal-title":"Soft Comput"},{"issue":"4","key":"10314_CR5","doi-asserted-by":"crossref","first-page":"1447","DOI":"10.1109\/59.99399","volume":"5","author":"M Bjelogrlic","year":"1990","unstructured":"Bjelogrlic M, Calovic MS, Ristanovic P, Babic BS (1990) Application of Newton\u2019s optimal power flow in voltage\/reactive power control. IEEE Trans Power Syst 5(4):1447\u20131454","journal-title":"IEEE Trans Power Syst"},{"key":"10314_CR6","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1016\/j.asoc.2016.11.008","volume":"50","author":"G Chen","year":"2017","unstructured":"Chen G, Liu L, Zhang Z, Huang S (2017) Optimal reactive power dispatch by improved GSA-based algorithm with the novel strategies to handle constraints. Appl Soft Comput 50:58\u201370","journal-title":"Appl Soft Comput"},{"key":"10314_CR7","doi-asserted-by":"crossref","first-page":"106321","DOI":"10.1016\/j.asoc.2020.106321","volume":"92","author":"G Chen","year":"2020","unstructured":"Chen G, Qian J, Zhang Z, Li S (2020) Application of modified pigeon-inspired optimization algorithm and constraint-objective sorting rule on multi-objective optimal power flow problem. Appl Soft Comput 92:106321","journal-title":"Appl Soft Comput"},{"issue":"2","key":"10314_CR9","doi-asserted-by":"crossref","first-page":"428","DOI":"10.1109\/59.54549","volume":"5","author":"N Deeb","year":"1990","unstructured":"Deeb N, Shahidehpour SM (1990) Linear reactive power optimization in a large power network using the decomposition approach. IEEE Trans Power Syst 5(2):428\u2013438","journal-title":"IEEE Trans Power Syst"},{"key":"10314_CR10","doi-asserted-by":"crossref","unstructured":"Dora BK, Bhat S, Halder S, Sahoo M (2023a) Solution of reactive power dispatch problems using enhanced dwarf mongoose optimization algorithm. In: 2023 international conference for advancement in technology (ICONAT), January. IEEE, pp 1\u20136","DOI":"10.1109\/ICONAT57137.2023.10080012"},{"key":"10314_CR11","doi-asserted-by":"crossref","first-page":"110833","DOI":"10.1016\/j.asoc.2023.110833","volume":"147","author":"BK Dora","year":"2023","unstructured":"Dora BK, Rajan A, Mallick S, Halder S (2023b) Optimal reactive power dispatch problem using exchange market based butterfly optimization algorithm. Appl Soft Comput 147:110833","journal-title":"Appl Soft Comput"},{"issue":"6","key":"10314_CR12","doi-asserted-by":"crossref","first-page":"563","DOI":"10.1049\/iet-gtd.2011.0681","volume":"6","author":"S Duman","year":"2012","unstructured":"Duman S, S\u00f6nmez YUSUF, G\u00fcven\u00e7 U, Y\u00f6r\u00fckeren N (2012) Optimal reactive power dispatch using a gravitational search algorithm. IET Gener Transm Distrib 6(6):563\u2013576","journal-title":"IET Gener Transm Distrib"},{"key":"10314_CR13","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2020\/6382507","volume":"2020","author":"TL Duong","year":"2020","unstructured":"Duong TL, Duong MQ, Phan VD, Nguyen TT (2020) Optimal reactive power flow for large-scale power systems using an effective metaheuristic algorithm. J Electr Comput Eng 2020:1\u201311","journal-title":"J Electr Comput Eng"},{"issue":"13","key":"10314_CR14","doi-asserted-by":"crossref","first-page":"1548","DOI":"10.1080\/15325008.2015.1041625","volume":"43","author":"AA El-Fergany","year":"2015","unstructured":"El-Fergany AA, Hasanien HM (2015) Single and multi-objective optimal power flow using grey wolf optimizer and differential evolution algorithms. Electric Power Compon Syst 43(13):1548\u20131559","journal-title":"Electric Power Compon Syst"},{"key":"10314_CR15","doi-asserted-by":"crossref","first-page":"8787","DOI":"10.1007\/s00521-019-04194-w","volume":"31","author":"SA El-Sattar","year":"2019","unstructured":"El-Sattar SA, Kamel S, El Sehiemy RA, Jurado F, Yu J (2019) Single-and multi-objective optimal power flow frameworks using Jaya optimization technique. Neural Comput Appl 31:8787\u20138806","journal-title":"Neural Comput Appl"},{"issue":"22","key":"10314_CR16","doi-asserted-by":"crossref","first-page":"20017","DOI":"10.1007\/s00521-022-07530-9","volume":"34","author":"AE Ezugwu","year":"2022","unstructured":"Ezugwu AE, Agushaka JO, Abualigah L, Mirjalili S, Gandomi AH (2022) Prairie dog optimization algorithm. Neural Comput Appl 34(22):20017\u201320065","journal-title":"Neural Comput Appl"},{"key":"10314_CR17","doi-asserted-by":"crossref","first-page":"318","DOI":"10.1016\/j.ijepes.2013.11.049","volume":"57","author":"A Ghasemi","year":"2014","unstructured":"Ghasemi A, Valipour K, Tohidi A (2014a) Multi objective optimal reactive power dispatch using a new multi objective strategy. Int J Electr Power Energy Syst 57:318\u2013334","journal-title":"Int J Electr Power Energy Syst"},{"issue":"24","key":"10314_CR18","doi-asserted-by":"crossref","first-page":"13899","DOI":"10.1007\/s00500-022-07417-w","volume":"26","author":"M Ghasemi","year":"2022","unstructured":"Ghasemi M, Akbari E, Faraji Davoudkhani I, Rahimnejad A, Asadpoor MB, Gadsden SA (2022) Application of Coulomb\u2019s and Franklin\u2019s laws algorithm to solve large-scale optimal reactive power dispatch problems. Soft Comput 26(24):13899\u201313923","journal-title":"Soft Comput"},{"key":"10314_CR19","doi-asserted-by":"crossref","first-page":"276","DOI":"10.1016\/j.energy.2014.10.007","volume":"78","author":"M Ghasemi","year":"2014","unstructured":"Ghasemi M, Ghavidel S, Ghanbarian MM, Gharibzadeh M, Vahed AA (2014b) Multi-objective optimal power flow considering the cost, emission, voltage deviation and power losses using multi-objective modified imperialist competitive algorithm. Energy 78:276\u2013289","journal-title":"Energy"},{"issue":"1","key":"10314_CR20","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1109\/59.317548","volume":"9","author":"S Granville","year":"1994","unstructured":"Granville S (1994) Optimal reactive dispatch through interior point methods. IEEE Trans Power Syst 9(1):136\u2013146","journal-title":"IEEE Trans Power Syst"},{"key":"10314_CR21","doi-asserted-by":"crossref","first-page":"101870","DOI":"10.1016\/j.jocs.2022.101870","volume":"64","author":"S Halder","year":"2022","unstructured":"Halder S, Dora BK, Bhat S (2022) An enhanced pathfinder algorithm based MCSA for rotor breakage detection of induction motor. J Comput Sci 64:101870","journal-title":"J Comput Sci"},{"issue":"2","key":"10314_CR22","doi-asserted-by":"crossref","first-page":"685","DOI":"10.1109\/59.317674","volume":"9","author":"K Iba","year":"1994","unstructured":"Iba K (1994) Reactive power optimization by genetic algorithm. IEEE Trans Power Syst 9(2):685\u2013692","journal-title":"IEEE Trans Power Syst"},{"issue":"1","key":"10314_CR23","first-page":"108","volume":"214","author":"D Karaboga","year":"2009","unstructured":"Karaboga D, Akay B (2009) A comparative study of artificial bee colony algorithm. Appl Math Comput 214(1):108\u2013132","journal-title":"Appl Math Comput"},{"key":"10314_CR24","doi-asserted-by":"crossref","first-page":"158353","DOI":"10.1109\/ACCESS.2021.3127940","volume":"9","author":"AK Khamees","year":"2021","unstructured":"Khamees AK, Abdelaziz AY, Eskaros MR, Alhelou HH, Attia MA (2021) Stochastic modeling for wind energy and multi-objective optimal power flow by novel meta-heuristic method. IEEE Access 9:158353\u2013158366","journal-title":"IEEE Access"},{"issue":"8","key":"10314_CR25","doi-asserted-by":"crossref","first-page":"e0235668","DOI":"10.1371\/journal.pone.0235668","volume":"15","author":"A Khan","year":"2020","unstructured":"Khan A, Hizam H, Bin Abdul Wahab NI, Lutfi Othman M (2020) Optimal power flow using hybrid firefly and particle swarm optimization algorithm. PLoS ONE 15(8):e0235668","journal-title":"PLoS ONE"},{"issue":"3","key":"10314_CR26","doi-asserted-by":"crossref","first-page":"684","DOI":"10.1016\/j.ijepes.2010.11.018","volume":"33","author":"AH Khazali","year":"2011","unstructured":"Khazali AH, Kalantar M (2011) Optimal reactive power dispatch based on harmony search algorithm. Int J Electr Power Energy Syst 33(3):684\u2013692","journal-title":"Int J Electr Power Energy Syst"},{"issue":"2","key":"10314_CR27","first-page":"874","volume":"11","author":"HH Kumar","year":"2020","unstructured":"Kumar HH, Mageshvaran R (2020) Load flow analysis and optimal allocation of DG for Indian utility 62 bus power system. Int J Emerg Technol 11(2):874\u2013886","journal-title":"Int J Emerg Technol"},{"issue":"6","key":"10314_CR28","doi-asserted-by":"crossref","first-page":"736","DOI":"10.1016\/j.ijepes.2010.01.010","volume":"32","author":"MS Kumari","year":"2010","unstructured":"Kumari MS, Maheswarapu S (2010) Enhanced genetic algorithm based computation technique for multi-objective optimal power flow solution. Int J Electr Power Energy Syst 32(6):736\u2013742","journal-title":"Int J Electr Power Energy Syst"},{"issue":"15","key":"10314_CR29","doi-asserted-by":"crossref","first-page":"2968","DOI":"10.3390\/en12152968","volume":"12","author":"Z Li","year":"2019","unstructured":"Li Z, Cao Y, Dai LV, Yang X, Nguyen TT (2019) Finding solutions for optimal reactive power dispatch problem by a novel improved antlion optimization algorithm. Energies 12(15):2968","journal-title":"Energies"},{"issue":"2","key":"10314_CR30","doi-asserted-by":"crossref","first-page":"641","DOI":"10.1016\/j.asoc.2009.08.038","volume":"10","author":"K Mahadevan","year":"2010","unstructured":"Mahadevan K, Kannan PS (2010) Comprehensive learning particle swarm optimization for reactive power dispatch. Appl Soft Comput 10(2):641\u2013652","journal-title":"Appl Soft Comput"},{"key":"10314_CR31","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1016\/j.ijepes.2013.04.011","volume":"53","author":"B Mandal","year":"2013","unstructured":"Mandal B, Roy PK (2013) Optimal reactive power dispatch using quasi-oppositional teaching learning based optimization. Int J Electr Power Energy Syst 53:123\u2013134","journal-title":"Int J Electr Power Energy Syst"},{"key":"10314_CR32","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1016\/j.engappai.2014.01.016","volume":"32","author":"MA Medina","year":"2014","unstructured":"Medina MA, Das S, Coello CAC, Ram\u00edrez JM (2014) Decomposition-based modern metaheuristic algorithms for multi-objective optimal power flow\u2014a comparative study. Eng Appl Artif Intell 32:10\u201320","journal-title":"Eng Appl Artif Intell"},{"issue":"3","key":"10314_CR33","first-page":"885","volume":"20","author":"S Mouassa","year":"2017","unstructured":"Mouassa S, Bouktir T, Salhi A (2017) Ant lion optimizer for solving optimal reactive power dispatch problem in power systems. Eng Sci Technol Int J 20(3):885\u2013895","journal-title":"Eng Sci Technol Int J"},{"key":"10314_CR34","doi-asserted-by":"crossref","first-page":"65830","DOI":"10.1109\/ACCESS.2020.2982988","volume":"8","author":"S Mugemanyi","year":"2020","unstructured":"Mugemanyi S, Qu Z, Rugema FX, Dong Y, Bananeza C, Wang L (2020) Optimal reactive power dispatch using chaotic bat algorithm. IEEE Access 8:65830\u201365867","journal-title":"IEEE Access"},{"key":"10314_CR35","doi-asserted-by":"crossref","first-page":"10501","DOI":"10.1007\/s00521-019-04589-9","volume":"32","author":"Y Muhammad","year":"2020","unstructured":"Muhammad Y, Khan R, Ullah F, Rehman AU, Aslam MS, Raja MAZ (2020) Design of fractional swarming strategy for solution of optimal reactive power dispatch. Neural Comput Appl 32:10501\u201310518","journal-title":"Neural Comput Appl"},{"key":"10314_CR37","doi-asserted-by":"crossref","first-page":"106492","DOI":"10.1016\/j.ijepes.2020.106492","volume":"125","author":"E Naderi","year":"2021","unstructured":"Naderi E, Pourakbari-Kasmaei M, Cerna FV, Lehtonen M (2021) A novel hybrid self-adaptive heuristic algorithm to handle single-and multi-objective optimal power flow problems. Int J Electr Power Energy Syst 125:106492","journal-title":"Int J Electr Power Energy Syst"},{"issue":"5","key":"10314_CR38","doi-asserted-by":"crossref","first-page":"831","DOI":"10.3390\/electronics11050831","volume":"11","author":"MH Nadimi-Shahraki","year":"2022","unstructured":"Nadimi-Shahraki MH, Fatahi A, Zamani H, Mirjalili S, Oliva D (2022) Hybridizing of whale and moth-flame optimization algorithms to solve diverse scales of optimal power flow problem. Electronics 11(5):831","journal-title":"Electronics"},{"issue":"23","key":"10314_CR39","doi-asserted-by":"crossref","first-page":"2975","DOI":"10.3390\/electronics10232975","volume":"10","author":"MH Nadimi-Shahraki","year":"2021","unstructured":"Nadimi-Shahraki MH, Taghian S, Mirjalili S, Abualigah L, Abd Elaziz M, Oliva D (2021) Ewoa-opf: effective whale optimization algorithm to solve optimal power flow problem. Electronics 10(23):2975","journal-title":"Electronics"},{"issue":"4","key":"10314_CR40","doi-asserted-by":"crossref","first-page":"308","DOI":"10.1093\/comjnl\/7.4.308","volume":"7","author":"JA Nelder","year":"1965","unstructured":"Nelder JA, Mead R (1965) A simplex method for function minimization. Comput J 7(4):308\u2013313","journal-title":"Comput J"},{"issue":"10","key":"10314_CR41","doi-asserted-by":"crossref","first-page":"5919","DOI":"10.1007\/s00521-019-04073-4","volume":"32","author":"TT Nguyen","year":"2020","unstructured":"Nguyen TT, Vo DN (2020) Improved social spider optimization algorithm for optimal reactive power dispatch problem with different objectives. Neural Comput Appl 32(10):5919\u20135950","journal-title":"Neural Comput Appl"},{"key":"10314_CR42","first-page":"1","volume":"2019","author":"TT Nguyen","year":"2019","unstructured":"Nguyen TT, Vo DN, Van Tran H, Van Dai L (2019) Optimal dispatch of reactive power using modified stochastic fractal search algorithm. Complexity 2019:1","journal-title":"Complexity"},{"issue":"10","key":"10314_CR43","doi-asserted-by":"crossref","first-page":"989","DOI":"10.1049\/iet-gtd.2011.0055","volume":"5","author":"T Niknam","year":"2011","unstructured":"Niknam T, Narimani MR, Aghaei J, Tabatabaei S, Nayeripour M (2011b) Modified honey bee mating optimisation to solve dynamic optimal power flow considering generator constraints. IET Gener Transm Distrib 5(10):989\u20131002","journal-title":"IET Gener Transm Distrib"},{"issue":"11","key":"10314_CR44","doi-asserted-by":"crossref","first-page":"6420","DOI":"10.1016\/j.energy.2011.09.027","volume":"36","author":"T Niknam","year":"2011","unstructured":"Niknam T, Rasoul Narimani M, Jabbari M, Malekpour AR (2011a) A modified shuffle frog leaping algorithm for multi-objective optimal power flow. Energy 36(11):6420\u20136432","journal-title":"Energy"},{"key":"10314_CR45","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1007\/s00500-016-2319-3","volume":"22","author":"H Pulluri","year":"2018","unstructured":"Pulluri H, Naresh R, Sharma V (2018) A solution network based on stud krill herd algorithm for optimal power flow problems. Soft Comput 22:159\u2013176","journal-title":"Soft Comput"},{"key":"10314_CR46","doi-asserted-by":"crossref","first-page":"108027","DOI":"10.1016\/j.asoc.2021.108027","volume":"113","author":"J Qian","year":"2021","unstructured":"Qian J, Wang P, Pu C, Peng X, Chen G (2021) Application of modified beetle antennae search algorithm and BP power flow prediction model on multi-objective optimal active power dispatch. Appl Soft Comput 113:108027","journal-title":"Appl Soft Comput"},{"key":"10314_CR47","doi-asserted-by":"crossref","unstructured":"Rajan A, Malakar T (2013) Optimal active and reactive power dispatch using hybrid evolutionary algorithm. Master\u2019s thesis, National Institute of Technology Silchar","DOI":"10.1109\/INDICON.2014.7030642"},{"key":"10314_CR48","doi-asserted-by":"crossref","first-page":"352","DOI":"10.1016\/j.asoc.2017.02.010","volume":"55","author":"A Rajan","year":"2017","unstructured":"Rajan A, Jeevan K, Malakar T (2017) Weighted elitism based ant lion optimizer to solve optimum VAr planning problem. Appl Soft Comput 55:352\u2013370","journal-title":"Appl Soft Comput"},{"key":"10314_CR49","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/j.ijepes.2014.10.041","volume":"66","author":"A Rajan","year":"2015","unstructured":"Rajan A, Malakar T (2015) Optimal reactive power dispatch using hybrid Nelder\u2013Mead simplex based firefly algorithm. Int J Electr Power Energy Syst 66:9\u201324","journal-title":"Int J Electr Power Energy Syst"},{"key":"10314_CR50","doi-asserted-by":"crossref","first-page":"320","DOI":"10.1016\/j.asoc.2016.02.041","volume":"43","author":"A Rajan","year":"2016","unstructured":"Rajan A, Malakar T (2016a) Exchange market algorithm based optimum reactive power dispatch. Appl Soft Comput 43:320\u2013336","journal-title":"Appl Soft Comput"},{"key":"10314_CR51","doi-asserted-by":"crossref","first-page":"545","DOI":"10.1016\/j.ijepes.2016.04.022","volume":"82","author":"A Rajan","year":"2016","unstructured":"Rajan A, Malakar T (2016b) Optimum economic and emission dispatch using exchange market algorithm. Int J Electr Power Energy Syst 82:545\u2013560","journal-title":"Int J Electr Power Energy Syst"},{"key":"10314_CR52","doi-asserted-by":"crossref","first-page":"20223","DOI":"10.1109\/ACCESS.2022.3152153","volume":"10","author":"MS Saddique","year":"2022","unstructured":"Saddique MS, Habib S, Haroon SS, Bhatti AR, Amin S, Ahmed EM (2022) Optimal solution of reactive power dispatch in transmission system to minimize power losses using sine-cosine algorithm. IEEE Access 10:20223\u201320239","journal-title":"IEEE Access"},{"key":"10314_CR53","doi-asserted-by":"crossref","first-page":"2011","DOI":"10.1007\/s00500-014-1388-4","volume":"19","author":"A Sarkheyli","year":"2015","unstructured":"Sarkheyli A, Zain AM, Sharif S (2015) The role of basic, modified and hybrid shuffled frog leaping algorithm on optimization problems: a review. Soft Comput 19:2011\u20132038","journal-title":"Soft Comput"},{"key":"10314_CR54","doi-asserted-by":"crossref","first-page":"597","DOI":"10.1016\/j.enconman.2013.09.028","volume":"77","author":"A Shabanpour-Haghighi","year":"2014","unstructured":"Shabanpour-Haghighi A, Seifi AR, Niknam T (2014) A modified teaching\u2013learning based optimization for multi-objective optimal power flow problem. Energy Convers Manag 77:597\u2013607","journal-title":"Energy Convers Manag"},{"key":"10314_CR55","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1016\/j.ijepes.2013.08.010","volume":"55","author":"B Shaw","year":"2014","unstructured":"Shaw B, Mukherjee V, Ghoshal SP (2014) Solution of reactive power dispatch of power systems by an opposition-based gravitational search algorithm. Int J Electr Power Energy Syst 55:29\u201340","journal-title":"Int J Electr Power Energy Syst"},{"key":"10314_CR56","doi-asserted-by":"crossref","first-page":"298","DOI":"10.1016\/j.asoc.2015.01.006","volume":"29","author":"RP Singh","year":"2015","unstructured":"Singh RP, Mukherjee V, Ghoshal SP (2015) Optimal reactive power dispatch by particle swarm optimization with an aging leader and challengers. Appl Soft Comput 29:298\u2013309","journal-title":"Appl Soft Comput"},{"issue":"3","key":"10314_CR57","doi-asserted-by":"crossref","first-page":"745","DOI":"10.1016\/j.ijepes.2010.12.031","volume":"33","author":"S Sivasubramani","year":"2011","unstructured":"Sivasubramani S, Swarup KS (2011) Multi-objective harmony search algorithm for optimal power flow problem. Int J Electr Power Energy Syst 33(3):745\u2013752","journal-title":"Int J Electr Power Energy Syst"},{"key":"10314_CR58","doi-asserted-by":"crossref","first-page":"286","DOI":"10.1016\/j.asoc.2015.03.041","volume":"32","author":"MH Sulaiman","year":"2015","unstructured":"Sulaiman MH, Mustaffa Z, Mohamed MR, Aliman O (2015) Using the gray wolf optimizer for solving optimal reactive power dispatch problem. Appl Soft Comput 32:286\u2013292","journal-title":"Appl Soft Comput"},{"key":"10314_CR59","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1007\/s00202-019-00762-4","volume":"101","author":"MA Taher","year":"2019","unstructured":"Taher MA, Kamel S, Jurado F, Ebeed M (2019) Modified grasshopper optimization framework for optimal power flow solution. Electr Eng 101:121\u2013148","journal-title":"Electr Eng"},{"key":"10314_CR61","unstructured":"The IEEE 118-Bus Test System (2017). https:\/\/labs.ece.uw.edu\/pstca\/pf118\/pg_tca118bus.htm"},{"key":"10314_CR60","unstructured":"The IEEE 30-Bus Test System (2017). http:\/\/labs.ece.uw.edu\/pstca\/pf30\/pg_tca30bus.htm"},{"issue":"5","key":"10314_CR62","doi-asserted-by":"crossref","first-page":"1222","DOI":"10.3390\/en14051222","volume":"14","author":"AM Tudose","year":"2021","unstructured":"Tudose AM, Picioroaga II, Sidea DO, Bulac C (2021) Solving single-and multi-objective optimal reactive power dispatch problems using an improved salp swarm algorithm. Energies 14(5):1222","journal-title":"Energies"},{"key":"10314_CR63","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.energy.2017.01.071","volume":"122","author":"X Yuan","year":"2017","unstructured":"Yuan X, Zhang B, Wang P, Liang J, Yuan Y, Huang Y, Lei X (2017) Multi-objective optimal power flow based on improved strength Pareto evolutionary algorithm. Energy 122:70\u201382","journal-title":"Energy"}],"container-title":["Soft Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00500-024-10314-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00500-024-10314-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00500-024-10314-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,11]],"date-time":"2024-12-11T02:35:23Z","timestamp":1733884523000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00500-024-10314-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11]]},"references-count":60,"journal-issue":{"issue":"21-22","published-print":{"date-parts":[[2024,11]]}},"alternative-id":["10314"],"URL":"https:\/\/doi.org\/10.1007\/s00500-024-10314-z","relation":{"has-preprint":[{"id-type":"doi","id":"10.21203\/rs.3.rs-3111489\/v1","asserted-by":"object"}]},"ISSN":["1432-7643","1433-7479"],"issn-type":[{"value":"1432-7643","type":"print"},{"value":"1433-7479","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11]]},"assertion":[{"value":"26 June 2024","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 November 2024","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that there is no conflict of interest regarding the publication of this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"Ethical approval is not applicable to this article.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}}]}}