{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T18:24:08Z","timestamp":1772821448640,"version":"3.50.1"},"reference-count":40,"publisher":"Springer Science and Business Media LLC","issue":"8","license":[{"start":{"date-parts":[[2017,11,7]],"date-time":"2017-11-07T00:00:00Z","timestamp":1510012800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51379080"],"award-info":[{"award-number":["51379080"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41571514"],"award-info":[{"award-number":["41571514"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Appl Intell"],"published-print":{"date-parts":[[2018,8]]},"DOI":"10.1007\/s10489-017-1081-2","type":"journal-article","created":{"date-parts":[[2017,11,7]],"date-time":"2017-11-07T00:44:08Z","timestamp":1510015448000},"page":"2304-2314","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Application of improved bat algorithm in optimal power flow problem"],"prefix":"10.1007","volume":"48","author":[{"given":"Yanbin","family":"Yuan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaotao","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pengtao","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0939-2704","authenticated-orcid":false,"given":"Xiaohui","family":"Yuan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2017,11,7]]},"reference":[{"key":"1081_CR1","first-page":"431","volume":"8","author":"J Carpentier","year":"1962","unstructured":"Carpentier J (1962) Contribution to the economic dispatch problem (in French). Bull Soc Franc Elect 8:431\u2013447","journal-title":"Bull Soc Franc Elect"},{"key":"1081_CR2","doi-asserted-by":"crossref","first-page":"3362","DOI":"10.1016\/j.enconman.2007.10.033","volume":"49","author":"K Zehar","year":"2008","unstructured":"Zehar K, Sayah S (2008) Optimal power flow with environmental constraint using a fast successive linear programming algorithm: application to the algerian power system. Energy Convers Manag 49:3362\u20133366","journal-title":"Energy Convers Manag"},{"issue":"1","key":"1081_CR3","doi-asserted-by":"crossref","first-page":"396","DOI":"10.1109\/59.852150","volume":"15","author":"H Wei","year":"2000","unstructured":"Wei H, Sasaki H, Kubokawa J (2000) Large scale hydrothermal optimal power flow problems based on interior point nonlinear programming. IEEE Trans Power Syst 15(1):396\u2013403","journal-title":"IEEE Trans Power Syst"},{"issue":"2","key":"1081_CR4","doi-asserted-by":"crossref","first-page":"514","DOI":"10.1109\/TPWRS.2013.2287914","volume":"29","author":"B Kazemtabrizi","year":"2014","unstructured":"Kazemtabrizi B, Acha E (2014) An advanced STATCOM model for optimal power flows using Newton\u2019s method. IEEE Trans Power Syst 29(2):514\u2013525","journal-title":"IEEE Trans Power Syst"},{"issue":"11","key":"1081_CR5","doi-asserted-by":"crossref","first-page":"1149","DOI":"10.1049\/iet-gtd.2011.0046","volume":"5","author":"S Sivasubramani","year":"2011","unstructured":"Sivasubramani S, Swarup KS (2011) Sequential quadratic programming based differential evolution algorithm for optimal power flow problem. IET Gener Transm Distrib 5(11):1149\u2013 1154","journal-title":"IET Gener Transm Distrib"},{"issue":"2","key":"1081_CR6","doi-asserted-by":"crossref","first-page":"487","DOI":"10.1109\/TPWRS.2010.2068568","volume":"26","author":"AA Sousa","year":"2011","unstructured":"Sousa AA, Torres GL, Canizares CA (2011) Robust optimal power flow solution using trust region and interior-point methods. IEEE Trans Power Syst 26(2):487\u2013499","journal-title":"IEEE Trans Power Syst"},{"issue":"4","key":"1081_CR7","doi-asserted-by":"crossref","first-page":"1148","DOI":"10.1007\/s10489-016-0801-3","volume":"45","author":"SP Das","year":"2016","unstructured":"Das SP, Achary NS, Padhy S (2016) Novel hybrid SVM-TLBO forecasting model incorporating dimensionality reduction techniques. Appl Intell 45(4):1148\u20131165","journal-title":"Appl Intell"},{"key":"1081_CR8","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1016\/j.enconman.2014.03.009","volume":"82","author":"X Yuan","year":"2014","unstructured":"Yuan X, Ji B, Zhang S (2014) An improved artificial physical optimization algorithm for dynamic dispatch of generators with valve-point effects and wind power. Energy Convers Manag 82:92\u2013105","journal-title":"Energy Convers Manag"},{"key":"1081_CR9","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1007\/s10489-014-0625-y","volume":"43","author":"R Liu","year":"2015","unstructured":"Liu R, Fan J, Jiao L (2015) Integration of improved predictive model and adaptive differential evolution based dynamic multi-objective evolutionary optimization algorithm. Appl Intell 43:192\u2013207","journal-title":"Appl Intell"},{"key":"1081_CR10","doi-asserted-by":"crossref","first-page":"589","DOI":"10.1016\/j.enconman.2014.07.060","volume":"87","author":"B Ji","year":"2014","unstructured":"Ji B, Yuan X, Li X (2014) Application of quantum-inspired binary gravitational search algorithm for thermal unit commitment with wind power integration. Energy Convers Manag 87:589\u2013 598","journal-title":"Energy Convers Manag"},{"issue":"11","key":"1081_CR11","doi-asserted-by":"crossref","first-page":"1285","DOI":"10.1080\/15325008.2012.689417","volume":"40","author":"AF Attia","year":"2012","unstructured":"Attia AF, Al-Turki YA, Abusorrah AM (2012) Optimal power flow using adapted genetic algorithm with adjusting population size. Electr Power Compon Syst 40(11):1285\u20131299","journal-title":"Electr Power Compon Syst"},{"issue":"4","key":"1081_CR12","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1061\/(ASCE)0733-9496(2008)134:4(319)","volume":"134","author":"XH Yuan","year":"2008","unstructured":"Yuan XH, Zhang YC, Yuan YB (2008) Improved self-adaptive chaotic genetic algorithm for hydrogeneration scheduling. J Water Resour Plan Manag-ASCE 134(4):319\u2013325","journal-title":"J Water Resour Plan Manag-ASCE"},{"key":"1081_CR13","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1016\/j.asoc.2015.11.027","volume":"40","author":"R Singh","year":"2016","unstructured":"Singh R, Mukherjee V, Ghoshal S (2016) Particle swarm optimization with an aging leader and challengers algorithm for the solution of optimal power flow problem. Appl Soft Comput 40:161\u2013177","journal-title":"Appl Soft Comput"},{"key":"1081_CR14","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1080\/15325000691001458","volume":"34","author":"W Ongsakul","year":"2006","unstructured":"Ongsakul W, Tantimaporn T (2006) Optimal power flow by improved evolutionary programming. Electr Power Compon Syst 34:79\u201395","journal-title":"Electr Power Compon Syst"},{"key":"1081_CR15","doi-asserted-by":"crossref","first-page":"816","DOI":"10.1016\/j.energy.2015.09.083","volume":"93","author":"A Panda","year":"2015","unstructured":"Panda A, Tripathy M (2015) Security constrained optimal power flow solution of wind-thermal generation system using modified bacteria foraging algorithm. Energy 93:816\u2013827","journal-title":"Energy"},{"key":"1081_CR16","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.enconman.2015.04.051","volume":"100","author":"X Yuan","year":"2015","unstructured":"Yuan X, Wang P, Yuan Y (2015) A new quantum inspired chaotic artificial bee colony algorithm for optimal power flow problem. Energy Convers Manag 100:1\u20139","journal-title":"Energy Convers Manag"},{"key":"1081_CR17","doi-asserted-by":"crossref","first-page":"340","DOI":"10.1016\/j.energy.2014.06.026","volume":"73","author":"M Ghasemi","year":"2014","unstructured":"Ghasemi M, Ghavidel S, Akbari E (2014) Solving non-linear, non-smooth and non-convex optimal power flow problems using chaotic invasive weed optimization algorithms based on chaos. Energy 73:340\u2013353","journal-title":"Energy"},{"key":"1081_CR18","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1016\/j.enconman.2012.02.024","volume":"59","author":"S Duman","year":"2012","unstructured":"Duman S, Guvenc U, Sonmez Y (2012) Optimal power flow using gravitational search algorithm. Energy Convers Manag 59:86\u2013 95","journal-title":"Energy Convers Manag"},{"key":"1081_CR19","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1016\/j.asoc.2014.05.029","volume":"22","author":"X Yuan","year":"2014","unstructured":"Yuan X, Ji B, Zhang S (2014) A new approach for unit commitment problem via binary gravitational search algorithm. Appl Soft Comput 22:249\u2013260","journal-title":"Appl Soft Comput"},{"issue":"11","key":"1081_CR20","doi-asserted-by":"crossref","first-page":"3036","DOI":"10.1016\/j.enconman.2008.06.014","volume":"49","author":"S Sayah","year":"2008","unstructured":"Sayah S, Zehar K (2008) Modified differential evolution algorithm for optimal power flow with non-smooth cost functions. Energy Convers Manag 49(11):3036\u20133042","journal-title":"Energy Convers Manag"},{"key":"1081_CR21","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, Jabbari M, Malekpour A (2011) A modified shuffle frog leaping algorithm for multi-objective optimal power flow. Energy 36:6420\u20136432","journal-title":"Energy"},{"key":"1081_CR22","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 A, 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":"1081_CR23","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1016\/j.ins.2014.05.040","volume":"281","author":"M Ghasemi","year":"2014","unstructured":"Ghasemi M, Ghavidel S, Ghanbarian M (2014) Application of imperialist competitive algorithm with its modified techniques for multi-objective optimal power flow problem: a comparative study. Inf Sci 281:225\u2013247","journal-title":"Inf Sci"},{"issue":"12","key":"1081_CR24","doi-asserted-by":"crossref","first-page":"1406","DOI":"10.1080\/15325001003735176","volume":"38","author":"P Roy","year":"2010","unstructured":"Roy P, Ghoshal S, Thakur S (2010) Multi-objective optimal power flow using biogeography-based optimization. Electr Power Compon Syst 38(12):1406\u20131426","journal-title":"Electr Power Compon Syst"},{"key":"1081_CR25","doi-asserted-by":"crossref","first-page":"2412","DOI":"10.3390\/en8042412","volume":"8","author":"X He","year":"2015","unstructured":"He X, Wang W, Jiang J, Xu L (2015) An improved artificial bee colony algorithm and its application to multi-objective optimal power flow. Energies 8:2412\u20132437","journal-title":"Energies"},{"key":"1081_CR26","doi-asserted-by":"crossref","first-page":"494","DOI":"10.1016\/j.asoc.2016.06.022","volume":"47","author":"J Zhang","year":"2016","unstructured":"Zhang J, Tang Q, Li P (2016) A modified MOEA\/D approach to the solution of multi-objective optimal power flow problem. Appl Soft Comput 47:494\u2013514","journal-title":"Appl Soft Comput"},{"key":"1081_CR27","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.energy.2017.01.071","volume":"122","author":"XH Yuan","year":"2017","unstructured":"Yuan XH, Zhang BQ, Wang PT, Liang J, Yuan YB, Huang YH, Lei XH (2017) Multi-objective optimal power flow based on improved strength Pareto evolutionary algorithm. Energy 122:70\u201382","journal-title":"Energy"},{"issue":"5","key":"1081_CR28","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1504\/IJBIC.2011.042259","volume":"3","author":"X Yang","year":"2011","unstructured":"Yang X (2011) Bat algorithm for multi-objective optimisation. Int J Bio-Inspired Comput 3(5):267\u2013274","journal-title":"Int J Bio-Inspired Comput"},{"key":"1081_CR29","doi-asserted-by":"crossref","first-page":"423","DOI":"10.1016\/j.ins.2014.10.014","volume":"294","author":"M Kang","year":"2015","unstructured":"Kang M, Kim J, Kim JM (2015) Reliable fault diagnosis for incipient low-speed bearings using fault feature analysis based on a binary bat algorithm. Inf Sci 294:423\u2013438","journal-title":"Inf Sci"},{"key":"1081_CR30","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1016\/j.asoc.2015.08.002","volume":"37","author":"NS Jaddi","year":"2015","unstructured":"Jaddi NS, Abdullah S, Hamdan AR (2015) Optimization of neural network model using modified bat-inspired algorithm. Appl Soft Comput 37:71\u201386","journal-title":"Appl Soft Comput"},{"key":"1081_CR31","doi-asserted-by":"crossref","first-page":"666","DOI":"10.1016\/j.energy.2015.12.096","volume":"96","author":"BR Adarsh","year":"2016","unstructured":"Adarsh BR, Raghunathan T, Jayabarathi T, Yang XS (2016) Economic dispatch using chaotic bat algorithm. Energy 96:666\u2013675","journal-title":"Energy"},{"issue":"5","key":"1081_CR32","doi-asserted-by":"crossref","first-page":"900","DOI":"10.1080\/0305215X.2015.1076402","volume":"48","author":"TP Talafuse","year":"2016","unstructured":"Talafuse TP, Pohl EA (2016) A bat algorithm for the redundancy allocation problem. Eng Optim 48(5):900\u2013910","journal-title":"Eng Optim"},{"key":"1081_CR33","doi-asserted-by":"crossref","first-page":"1029","DOI":"10.1016\/j.applthermaleng.2016.09.031","volume":"110","author":"TK Tharakeshwar","year":"2017","unstructured":"Tharakeshwar TK, Seetharamu KN, Prasad BD (2017) Multi-objective optimization using bat algorithm for shell and tube heat exchangers. Appl Thermal Eng 110:1029\u20131038","journal-title":"Appl Thermal Eng"},{"key":"1081_CR34","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1016\/j.measurement.2016.09.031","volume":"95","author":"B Vedik","year":"2017","unstructured":"Vedik B, Chandel AK (2017) Optimal PMU placement for power system observability using Taguchi binary bat algorithm. Measurement 95:8\u201320","journal-title":"Measurement"},{"issue":"1","key":"1081_CR35","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1109\/TEVC.2010.2046328","volume":"16","author":"RH Shang","year":"2012","unstructured":"Shang RH, Jiao LC, Liu F, Ma WP (2012) Novel immune clonal algorithm for MO problems. IEEE Trans Evol Comput 16(1):35\u201350","journal-title":"IEEE Trans Evol Comput"},{"key":"1081_CR36","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1016\/j.ins.2012.12.013","volume":"228","author":"LC Jiao","year":"2013","unstructured":"Jiao LC, Wang HD, Shang RH, Liu F (2013) A co-evolutionary multi-objective optimization algorithm based on direction vectors. Inf Sci 228:90\u2013112","journal-title":"Inf Sci"},{"key":"1081_CR37","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1016\/j.physa.2016.02.020","volume":"453","author":"RH Shang","year":"2016","unstructured":"Shang RH, Luo S, Zhang WT, Stolkin R, Jiao LC (2016) A multiobjective evolutionary algorithm to find community structures based on affinity propagation. Physica A 453:203\u2013227","journal-title":"Physica A"},{"issue":"4","key":"1081_CR38","doi-asserted-by":"crossref","first-page":"524","DOI":"10.1109\/TEVC.2014.2350987","volume":"19","author":"HD Wang","year":"2015","unstructured":"Wang HD, Jiao LC, Xin Yao (2015) Two_Arch2: an improved two-archive algorithm for many-objective optimization. IEEE Trans Evol Comput 19(4):524\u2013541","journal-title":"IEEE Trans Evol Comput"},{"key":"1081_CR39","doi-asserted-by":"crossref","first-page":"390","DOI":"10.1016\/j.enconman.2014.04.052","volume":"84","author":"Z Chen","year":"2014","unstructured":"Chen Z, Yuan X, Ji B (2014) Design of a fractional order PID controller for hydraulic turbine regulating system using chaotic non-dominated sorting genetic algorithm II. Energy Convers Manag 84:390\u2013404","journal-title":"Energy Convers Manag"},{"key":"1081_CR40","doi-asserted-by":"crossref","first-page":"609","DOI":"10.1016\/j.ins.2014.03.008","volume":"277","author":"RH Shang","year":"2014","unstructured":"Shang RH, Wang YY, Wang J, Jiao LC, Wang S, Qi LP (2014) A multi-population cooperative coevolutionary algorithm for multi-objective capacitated arc routing problem. Inf Sci 277:609\u2013 642","journal-title":"Inf Sci"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10489-017-1081-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-017-1081-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-017-1081-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2018,7,16]],"date-time":"2018-07-16T23:28:51Z","timestamp":1531783731000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10489-017-1081-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,11,7]]},"references-count":40,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2018,8]]}},"alternative-id":["1081"],"URL":"https:\/\/doi.org\/10.1007\/s10489-017-1081-2","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"value":"0924-669X","type":"print"},{"value":"1573-7497","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,11,7]]}}}