{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,6]],"date-time":"2026-07-06T16:02:21Z","timestamp":1783353741510,"version":"3.54.6"},"reference-count":58,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,1,8]],"date-time":"2025-01-08T00:00:00Z","timestamp":1736294400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,1,8]],"date-time":"2025-01-08T00:00:00Z","timestamp":1736294400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"name":"Key Laboratory of Evolutionary Artificial Intelligence of Guizhou Province","award":["Qianjiaoji [2022] No. 059"],"award-info":[{"award-number":["Qianjiaoji [2022] No. 059"]}]},{"name":"Key Laboratory of Evolutionary Artificial Intelligence of Guizhou Province","award":["Qianjiaoji [2022] No. 059"],"award-info":[{"award-number":["Qianjiaoji [2022] No. 059"]}]},{"name":"Key Laboratory of Evolutionary Artificial Intelligence of Guizhou Province","award":["Qianjiaoji [2022] No. 059"],"award-info":[{"award-number":["Qianjiaoji [2022] No. 059"]}]},{"name":"Key Laboratory of Evolutionary Artificial Intelligence of Guizhou Province","award":["Qianjiaoji [2022] No. 059"],"award-info":[{"award-number":["Qianjiaoji [2022] No. 059"]}]},{"name":"Key Laboratory of Evolutionary Artificial Intelligence of Guizhou Province","award":["Qianjiaoji [2022] No. 059"],"award-info":[{"award-number":["Qianjiaoji [2022] No. 059"]}]},{"name":"Key Laboratory of Evolutionary Artificial Intelligence of Guizhou Province","award":["Qianjiaoji [2022] No. 059"],"award-info":[{"award-number":["Qianjiaoji [2022] No. 059"]}]},{"name":"Qiankehe Platform Talent","award":["ZZSG [2024] 014"],"award-info":[{"award-number":["ZZSG [2024] 014"]}]},{"name":"Qiankehe Platform Talent","award":["ZZSG [2024] 014"],"award-info":[{"award-number":["ZZSG [2024] 014"]}]},{"name":"Qiankehe Platform Talent","award":["ZZSG [2024] 014"],"award-info":[{"award-number":["ZZSG [2024] 014"]}]},{"name":"Qiankehe Platform Talent","award":["ZZSG [2024] 014"],"award-info":[{"award-number":["ZZSG [2024] 014"]}]},{"name":"Qiankehe Platform Talent","award":["ZZSG [2024] 014"],"award-info":[{"award-number":["ZZSG [2024] 014"]}]},{"name":"Qiankehe Platform Talent","award":["ZZSG [2024] 014"],"award-info":[{"award-number":["ZZSG [2024] 014"]}]},{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["NSFC 62062071"],"award-info":[{"award-number":["NSFC 62062071"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["NSFC 62062071"],"award-info":[{"award-number":["NSFC 62062071"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["NSFC 62062071"],"award-info":[{"award-number":["NSFC 62062071"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["NSFC 62062071"],"award-info":[{"award-number":["NSFC 62062071"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["NSFC 62062071"],"award-info":[{"award-number":["NSFC 62062071"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["NSFC 62062071"],"award-info":[{"award-number":["NSFC 62062071"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int J Comput Intell Syst"],"DOI":"10.1007\/s44196-024-00722-2","type":"journal-article","created":{"date-parts":[[2025,1,8]],"date-time":"2025-01-08T16:06:03Z","timestamp":1736352363000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Multi-objective Particle Swarm Optimization with Integrated Fireworks Algorithm and Size Double Archiving"],"prefix":"10.1007","volume":"18","author":[{"given":"Yansong","family":"Zhang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanmin","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoyan","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qian","family":"Song","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aijia","family":"Ouyang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jie","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,1,8]]},"reference":[{"issue":"1","key":"722_CR1","doi-asserted-by":"publisher","first-page":"126","DOI":"10.1109\/TEVC.2022.3162993","volume":"27","author":"K Li","year":"2022","unstructured":"Li, K., Chen, R.: Batched data-driven evolutionary multi-objective optimization based on manifold interpolation. IEEE Trans. Evol. Comput.Evol. Comput. 27(1), 126\u2013140 (2022)","journal-title":"IEEE Trans. Evol. Comput.Evol. Comput."},{"key":"722_CR2","first-page":"1","volume":"2018","author":"M Pescador-Rojas","year":"2018","unstructured":"Pescador-Rojas, M., Coello, C.A.C.: Collaborative and adaptive strategies of different scalarizing functions in MOEA\/D. IEEE Congr. Evol. Comput. (CEC) 2018, 1\u20138 (2018)","journal-title":"IEEE Congr. Evol. Comput. (CEC)"},{"key":"722_CR3","doi-asserted-by":"publisher","first-page":"874","DOI":"10.1109\/TCYB.2020.3015756","volume":"51","author":"Y Hu","year":"2021","unstructured":"Hu, Y., Zhang, Y., Gong, D.: Multi-objective particle swarm optimization for feature selection with fuzzy cost. IEEE Trans. Cybern. 51, 874\u2013888 (2021)","journal-title":"IEEE Trans. Cybern."},{"key":"722_CR4","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1162\/EVCO_a_00104","volume":"22","author":"NA Moubayed","year":"2014","unstructured":"Moubayed, N.A., Petrovski, A., Mccall, J.: D2MOPSO: MOPSO based on decomposition and dominance with archiving using crowding distance in objective and solution spaces. Evol. Comput.. Comput. 22, 47\u201377 (2014)","journal-title":"Evol. Comput.. Comput."},{"key":"722_CR5","doi-asserted-by":"publisher","first-page":"645","DOI":"10.1109\/TEVC.2015.2504730","volume":"20","author":"M Li","year":"2016","unstructured":"Li, M., Yang, S., Liu, X.: Pareto or non-Pareto: bi-criterion evolution in multi-objective optimization. IEEE Trans. Evol. Comput.Evol. Comput. 20, 645\u2013665 (2016)","journal-title":"IEEE Trans. Evol. Comput.Evol. Comput."},{"key":"722_CR6","doi-asserted-by":"publisher","first-page":"912","DOI":"10.1016\/j.ins.2021.10.007","volume":"581","author":"W Feng","year":"2021","unstructured":"Feng, W., Gong, D., Yu, Z.: Multi-objective evolutionary optimization based on online perceiving Pareto front characteristics. Inf. Sci. 581, 912\u2013931 (2021)","journal-title":"Inf. Sci."},{"key":"722_CR7","doi-asserted-by":"publisher","first-page":"680","DOI":"10.1016\/j.asoc.2018.06.022","volume":"70","author":"MZ bin Mohd Zain","year":"2018","unstructured":"bin Mohd Zain, M.Z., Kanesan, J., Chuah, J.H., Dhanapal, S., Kendall, G.: A multi-objective particle swarm optimization algorithm based on dynamic boundary search for constrained optimization. Appl. Soft Comput.Comput. 70, 680\u2013700 (2018)","journal-title":"Appl. Soft Comput.Comput."},{"issue":"4","key":"722_CR8","doi-asserted-by":"publisher","first-page":"577","DOI":"10.1109\/TEVC.2013.2281535","volume":"18","author":"K Deb","year":"2013","unstructured":"Deb, K., Jain, H.: An evolutionary many-objective optimization algorithm using reference-point-based non-dominated sorting approach, part I: solving problems with box constraints. IEEE Trans. Evol. Comput.Evol. Comput. 18(4), 577\u2013601 (2013)","journal-title":"IEEE Trans. Evol. Comput.Evol. Comput."},{"key":"722_CR9","doi-asserted-by":"publisher","first-page":"167","DOI":"10.1016\/j.asoc.2018.10.012","volume":"74","author":"J Liu","year":"2019","unstructured":"Liu, J., Liu, J.: Applying multi-objective ant colony optimization algorithm for solving the unequal area facility layout problems. Appl. Soft Comput.Comput. 74, 167\u2013189 (2019)","journal-title":"Appl. Soft Comput.Comput."},{"key":"722_CR10","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2019.103307","volume":"87","author":"E Hancer","year":"2020","unstructured":"Hancer, E.: A new multi-objective differential evolution approach for simultaneous clustering and feature selection. Eng. Appl. Artif. Intell.Artif. Intell. 87, 103307 (2020)","journal-title":"Eng. Appl. Artif. Intell.Artif. Intell."},{"key":"722_CR11","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1016\/j.chaos.2014.12.019","volume":"73","author":"I Fister","year":"2015","unstructured":"Fister, I., Perc, M., Ljubic, K., Kamal, S.M., Iglesias, A., Fister, I.: Particle swarm optimization for automatic creation of complex graphic characters. Chaos Solitons Fractals 73, 29\u201335 (2015)","journal-title":"Chaos Solitons Fractals"},{"key":"722_CR12","first-page":"409","volume":"24","author":"C Yang","year":"2020","unstructured":"Yang, C., Ding, J., Jin, Y., Chai, T.: Offline data-driven multiobjective optimization: knowledge transfer between surrogates and generation of final solutions. IEEE Trans. Evol. Comput.Evol. Comput. 24, 409\u2013423 (2020)","journal-title":"IEEE Trans. Evol. Comput.Evol. Comput."},{"issue":"7","key":"722_CR13","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0021787","volume":"6","author":"J Zhang","year":"2011","unstructured":"Zhang, J., Zhang, C., Chu, T., Perc, M.: Resolution of the stochastic strategy spatial prisoner\u2019s dilemma by means of particle swarm optimization. PLoS ONE 6(7), e21787 (2011)","journal-title":"PLoS ONE"},{"key":"722_CR14","doi-asserted-by":"publisher","first-page":"425","DOI":"10.1016\/j.ins.2012.07.027","volume":"220","author":"AA Taleizadeh","year":"2013","unstructured":"Taleizadeh, A.A., Niaki, S.T.A., Aryanezhad, M.-B., Shafii, N.: A hybrid method of fuzzy simulation and genetic algorithm to optimize constrained inventory control systems with stochastic replenishments and fuzzy demand. Inf. Sci. 220, 425\u2013441 (2013)","journal-title":"Inf. Sci."},{"key":"722_CR15","doi-asserted-by":"publisher","first-page":"467","DOI":"10.1016\/j.asoc.2018.03.020","volume":"67","author":"HG Han","year":"2018","unstructured":"Han, H.G., Zhang, L., Liu, H.X., Qiao, J.F.: Multi-objective design of fuzzy neural network controller for wastewater treatment process. Appl. Soft Comput.Comput. 67, 467\u2013478 (2018)","journal-title":"Appl. Soft Comput.Comput."},{"key":"722_CR16","doi-asserted-by":"publisher","DOI":"10.1016\/j.swevo.2021.100989","volume":"69","author":"J Lu","year":"2022","unstructured":"Lu, J., Zhang, J., Sheng, J.: Enhanced multi-swarm cooperative particle swarm optimizer. Swarm Evol Comput 69, 100989 (2022)","journal-title":"Swarm Evol Comput"},{"key":"722_CR17","doi-asserted-by":"crossref","unstructured":"Eberhart,R.C., Kennedy, J.: A new optimizer using particle swarm theory. In: Proceedings of the Sixth International Symposium on Micro Machine and Human Science, IEEE, pp. 39\u201343 (1995)","DOI":"10.1109\/MHS.1995.494215"},{"key":"722_CR18","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2020.106947","volume":"99","author":"SX Cheng","year":"2021","unstructured":"Cheng, S.X., Zhan, H., Yao, H.Q., Fan, H.Y., Liu, Y.: Large-scale many-objective particle swarm optimizer with fast convergence based on alpha-stable mutation and logistic function. Appl. Soft Comput.Comput. 99, 106947 (2021)","journal-title":"Appl. Soft Comput.Comput."},{"issue":"3","key":"722_CR19","doi-asserted-by":"publisher","first-page":"256","DOI":"10.1109\/TEVC.2004.826067","volume":"8","author":"CAC Coello","year":"2004","unstructured":"Coello, C.A.C., Pulido, G.T., Lechuga, M.S.: Handling multiple objectives with particle swarm optimization. IEEE Trans. Evol. Comput.Evol. Comput. 8(3), 256\u2013279 (2004)","journal-title":"IEEE Trans. Evol. Comput.Evol. Comput."},{"key":"722_CR20","doi-asserted-by":"publisher","first-page":"3738","DOI":"10.1109\/TCYB.2019.2949204","volume":"51","author":"BL Wu","year":"2021","unstructured":"Wu, B.L., Hu, W., Hu, J.J., Yen, G.G.: Adaptive multi-objective particle swarm optimization based on evolutionary state estimation. IEEE Trans. Cybern. 51, 3738\u20133751 (2021)","journal-title":"IEEE Trans. Cybern."},{"key":"722_CR21","doi-asserted-by":"crossref","unstructured":"Raquel,C.R., Naval, P.C.: An effective use of crowding distance in multi-objective particle swarm optimization. In: GECCO 2005\u2014Genet. Evol. Comput. Conf., pp. 257\u2013264 (2005)","DOI":"10.1145\/1068009.1068047"},{"key":"722_CR22","doi-asserted-by":"crossref","unstructured":"Yuan,Y.Q., Sun, J., Zhou, D.M.: Multi-objective random drift particle swarm optimization algorithm with adaptive grids. In: 2016 IEEE Congr. Evol. Comput, IEEE, pp. 2064\u20132070 (2016)","DOI":"10.1109\/CEC.2016.7744042"},{"key":"722_CR23","doi-asserted-by":"publisher","first-page":"721","DOI":"10.1109\/TEVC.2012.2227145","volume":"17","author":"SX Yang","year":"2013","unstructured":"Yang, S.X., Li, M.Q., Liu, X.H., Zheng, J.H.: A grid-based evolutionary algorithm for many-objective optimization. IEEE Trans. Evol. Comput.Evol. Comput. 17, 721\u2013736 (2013)","journal-title":"IEEE Trans. Evol. Comput.Evol. Comput."},{"key":"722_CR24","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TEVC.2013.2296151","volume":"19","author":"W Hu","year":"2015","unstructured":"Hu, W., Yen, G.G.: Adaptive multi-objective particle swarm optimization based on parallel cell coordinate system. IEEE Trans. Evol. Comput.Evol. Comput. 19, 1\u201318 (2015)","journal-title":"IEEE Trans. Evol. Comput.Evol. Comput."},{"key":"722_CR25","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2022.108532","volume":"119","author":"Y Cui","year":"2022","unstructured":"Cui, Y., Meng, X., Qiao, J.: A multi-objective particle swarm optimization algorithm based on two-archive mechanism. Appl. Soft Comput.Comput. 119, 108532 (2022)","journal-title":"Appl. Soft Comput.Comput."},{"key":"722_CR26","doi-asserted-by":"crossref","unstructured":"Wu,B.L., Hu, W., He, Z.N., Jiang, M., Yen, G.G. A many-objective particle swarm optimization based on virtual pareto front. In: IEEE. Cong. Evol. Comput, (CEC), pp. 78\u201385 (2018)","DOI":"10.1109\/CEC.2018.8477802"},{"key":"722_CR27","doi-asserted-by":"publisher","first-page":"166","DOI":"10.1016\/j.ins.2019.11.047","volume":"514","author":"JP Luo","year":"2020","unstructured":"Luo, J.P., Huang, X.W., Yang, Y., Li, X., Wang, Z.K., Feng, J.Q.: A many-objective particle swarm optimizer based on indicator and direction vectors for many-objective optimization. Inf. Sci. 514, 166\u2013202 (2020)","journal-title":"Inf. Sci."},{"key":"722_CR28","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1109\/TEVC.2016.2587749","volume":"21","author":"H Ishibuchi","year":"2017","unstructured":"Ishibuchi, H., Setoguchi, Y., Masuda, H., Nojima, Y.: Performance of decomposition-based many-objective algorithms strongly depends on pareto front shapes. IEEE Trans. Evol. Comput.Evol. Comput. 21, 169\u2013190 (2017)","journal-title":"IEEE Trans. Evol. Comput.Evol. Comput."},{"key":"722_CR29","doi-asserted-by":"publisher","first-page":"220","DOI":"10.1016\/j.ins.2022.12.021","volume":"623","author":"N Kouka","year":"2023","unstructured":"Kouka, N., BenSaid, F., Fdhila, R., Fourati, R., Hussain, A., Alimi, A.M.: A novel approach of many-objective particle swarm optimization with cooperative agents based on an inverted generational distance indicator. Inf. Sci. 623, 220\u2013241 (2023)","journal-title":"Inf. Sci."},{"key":"722_CR30","doi-asserted-by":"crossref","unstructured":"Garcia,I.C., Coello, C.A.C., Arias-Montano, A.: MOPSOhv: a new hypervolume-based multi-objective particle swarm optimizer. In: IEEE. Cong. Evol. Comput, (CEC), pp. 266\u2013273 (2014)","DOI":"10.1109\/CEC.2014.6900540"},{"key":"722_CR31","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1016\/j.ins.2022.12.079","volume":"625","author":"Y Li","year":"2023","unstructured":"Li, Y., Zhang, Y., Hu, W.: Adaptive multi-objective particle swarm optimization based on virtual Pareto front. Inf. Sci. 625, 206\u2013236 (2023)","journal-title":"Inf. Sci."},{"issue":"9","key":"722_CR32","doi-asserted-by":"publisher","first-page":"2754","DOI":"10.1109\/TCYB.2017.2692385","volume":"47","author":"H Han","year":"2017","unstructured":"Han, H., Lu, W., Qiao, J.: An adaptive multi-objective particle swarm optimization based on multiple adaptive methods. IEEE Trans. Cybern. 47(9), 2754\u20132767 (2017)","journal-title":"IEEE Trans. Cybern."},{"key":"722_CR33","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1016\/j.ins.2020.05.004","volume":"532","author":"Y Zhou","year":"2020","unstructured":"Zhou, Y., Kang, J.H., Guo, H.N.: Many-objective optimization of feature selection based on two-level particle cooperation. Inf. Sci. 532, 91\u2013109 (2020)","journal-title":"Inf. Sci."},{"key":"722_CR34","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1109\/TEVC.2016.2631279","volume":"22","author":"QZ Lin","year":"2018","unstructured":"Lin, Q.Z., Liu, S.B., Zhu, Q.L., Tang, C.Y., Song, R.Z., Chen, J.Y., Coello, C.A.C., Wong, K.C., Zhang, J.: Particle swarm optimization with a balanceable fitness estimation for many-objective optimization problems. IEEE Trans. Evol. Comput.Evol. Comput. 22, 32\u201346 (2018)","journal-title":"IEEE Trans. Evol. Comput.Evol. Comput."},{"issue":"1","key":"722_CR35","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1109\/TEVC.2013.2285016","volume":"18","author":"D Mart\u00edn","year":"2014","unstructured":"Mart\u00edn, D., Rosete, A., Alcal\u00e1-Fdez, J., Herrera, F.: A new multi-objective evolutionary algorithm for mining a reduced set of interesting positive and negative quantitative association rules. IEEE Trans. Evol. Comput.Evol. Comput. 18(1), 54\u201369 (2014)","journal-title":"IEEE Trans. Evol. Comput.Evol. Comput."},{"issue":"2","key":"722_CR36","doi-asserted-by":"publisher","first-page":"259","DOI":"10.1109\/TEVC.2012.2189404","volume":"17","author":"S Helwig","year":"2013","unstructured":"Helwig, S., Branke, J., Mostaghim, S.: Experimental analysis of bound handling techniques in particle swarm optimization. IEEE Trans. Evol. Comput.Evol. Comput. 17(2), 259\u2013271 (2013)","journal-title":"IEEE Trans. Evol. Comput.Evol. Comput."},{"issue":"2","key":"722_CR37","doi-asserted-by":"publisher","first-page":"201","DOI":"10.1109\/TEVC.2014.2308305","volume":"19","author":"X Zhang","year":"2015","unstructured":"Zhang, X., Tian, Y., Cheng, R., Jin, Y.: An efficient approach to non-dominated sorting for evolutionary multiobjective optimization. IEEE Trans. Evol. Comput.Evol. Comput. 19(2), 201\u2013213 (2015)","journal-title":"IEEE Trans. Evol. Comput.Evol. Comput."},{"issue":"1","key":"722_CR38","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1109\/TCBB.2015.2446484","volume":"14","author":"S Cheng","year":"2017","unstructured":"Cheng, S., Zhao, L., Jiang, X.: An effective application of bacteria quorum sensing and circular elimination in MOPSO. IEEE\/ACM Trans. Comput. Biol. Bioinform.Comput. Biol. Bioinform. 14(1), 56\u201363 (2017)","journal-title":"IEEE\/ACM Trans. Comput. Biol. Bioinform.Comput. Biol. Bioinform."},{"key":"722_CR39","doi-asserted-by":"publisher","first-page":"87916","DOI":"10.1109\/ACCESS.2019.2925540","volume":"7","author":"Q Feng","year":"2019","unstructured":"Feng, Q., Li, Q., Chen, P., Wang, H., Xue, Z., Yin, L., Ge, C.: Multi-objective particle swarm optimization algorithm based on adaptive angle division. IEEE Access 7, 87916\u201387930 (2019)","journal-title":"IEEE Access"},{"key":"722_CR40","doi-asserted-by":"publisher","first-page":"172","DOI":"10.1016\/j.neucom.2012.09.019","volume":"103","author":"Y Zhang","year":"2013","unstructured":"Zhang, Y., Wei Gong, D., Hua Zhang, J.: Robot path planning in uncertain environment using multi-objective particle swarm optimization. Neurocomputing 103, 172\u2013185 (2013)","journal-title":"Neurocomputing"},{"key":"722_CR41","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2020.106661","volume":"96","author":"L Li","year":"2020","unstructured":"Li, L., Li, G., Chang, L.: A many-objective particle swarm optimization with grid dominance ranking and clustering. Appl. Soft Comput.Comput. 96, 106661 (2020)","journal-title":"Appl. Soft Comput.Comput."},{"key":"722_CR42","unstructured":"Tan Y., Zhu Y.: Fireworks algorithm for optimization. In: Advances in Swarm Intelligence: First International Conference, ICSI 2010, Beijing, China, June 12\u201315, 2010, Proceedings, Part I 1, pp. 355\u2013364. Springer, Berlin Heidelberg (2010)"},{"issue":"3","key":"722_CR43","doi-asserted-by":"publisher","first-page":"348","DOI":"10.1109\/TEVC.2013.2262178","volume":"18","author":"M Li","year":"2013","unstructured":"Li, M., Yang, S., Liu, X.: Shift-based density estimation for Pareto-based algorithms in many-objective optimization. IEEE Trans. Evol. Comput.Evol. Comput. 18(3), 348\u2013365 (2013)","journal-title":"IEEE Trans. Evol. Comput.Evol. Comput."},{"key":"722_CR44","doi-asserted-by":"crossref","unstructured":"Raquel,C.R., Naval, P.C.: An effective use of crowding distance in multiobjective particle swarm optimization. In: GECCO 2005\u2014Genet. Evol. Comput. Conf., pp. 257\u2013264 (2005)","DOI":"10.1145\/1068009.1068047"},{"issue":"2","key":"722_CR45","doi-asserted-by":"publisher","first-page":"173","DOI":"10.1162\/106365600568202","volume":"8","author":"E Zitzler","year":"2000","unstructured":"Zitzler, E., Deb, K., Thiele, L.: Comparison of multi-objective evolutionary algorithms: empirical results. Evol. Comput.. Comput. 8(2), 173\u2013195 (2000)","journal-title":"Evol. Comput.. Comput."},{"key":"722_CR46","first-page":"1","volume":"264","author":"Q Zhang","year":"2008","unstructured":"Zhang, Q., Zhou, A., Zhao, S., Suganthan, P.N., Liu, W., Tiwari, S.: Multi-objective optimization test instances for the CEC 2009 special session and competition. Mech Eng New York 264, 1\u201330 (2008)","journal-title":"Mech Eng New York"},{"key":"722_CR47","doi-asserted-by":"crossref","unstructured":"Deb, K., Thiele, L., Laumanns, M., Zitzler, E.: Scalable test problems for evolutionary multi-objective optimization. In: Evol Mult Opt London, pp. 105\u2013145 (2005)","DOI":"10.1007\/1-84628-137-7_6"},{"key":"722_CR48","doi-asserted-by":"publisher","first-page":"732","DOI":"10.1016\/j.ejor.2015.06.071","volume":"247","author":"QZ Lin","year":"2015","unstructured":"Lin, Q.Z., Li, J.Q., Du, Z.H., Chen, J.Y., Ming, Z.: A novel multi-objective particle swarm optimization with multiple search strategies. Eur. J. Oper. Res.Oper. Res. 247, 732\u2013744 (2015)","journal-title":"Eur. J. Oper. Res.Oper. Res."},{"key":"722_CR49","doi-asserted-by":"crossref","unstructured":"Raquel, C.R., Naval, Jr P.C.: An effective use of crowding distance in multi-objective particle swarm optimization. In: Proceedings of the 7th Annual conference on Genetic and Evolutionary Computation, 257\u2013264 (2005)","DOI":"10.1145\/1068009.1068047"},{"key":"722_CR50","doi-asserted-by":"crossref","unstructured":"Nebro, A.J., Durillo, J.J., Nieto, G., Coello, C.A.C., Luna, F., Alba, E.: SMPSO: a new pso-based metaheuristic for multi-objective optimization. In: 2009 IEEE Symp. Comput. Intell. Multi-Criteria Decis., pp. 66\u201373 (2009)","DOI":"10.1109\/MCDM.2009.4938830"},{"key":"722_CR51","doi-asserted-by":"crossref","unstructured":"Mart\u00ednez, S.Z., Coello, C.A.C.: A multi-objective particle swarm optimizer based on decomposition. In: Genet. Evol. Comput. Conf. GECCO\u201911, pp. 69\u201376 (2011)","DOI":"10.1145\/2001576.2001587"},{"key":"722_CR52","doi-asserted-by":"publisher","first-page":"694","DOI":"10.1109\/TEVC.2014.2373386","volume":"19","author":"K Li","year":"2015","unstructured":"Li, K., Deb, K., Zhang, Q.F., Kwong, S.: An evolutionary many-objective optimization algorithm based on dominance and decomposition. IEEE Trans. Evol. Comput.Evol. Comput. 19, 694\u2013716 (2015)","journal-title":"IEEE Trans. Evol. Comput.Evol. Comput."},{"key":"722_CR53","doi-asserted-by":"publisher","first-page":"329","DOI":"10.1109\/TEVC.2016.2592479","volume":"21","author":"SY Jiang","year":"2017","unstructured":"Jiang, S.Y., Yang, S.X.: A strength pareto evolutionary algorithm based on reference direction for multiobjective and many-objective optimization. IEEE Trans. Evol. Comput.Evol. Comput. 21, 329\u2013346 (2017)","journal-title":"IEEE Trans. Evol. Comput.Evol. Comput."},{"issue":"4","key":"722_CR54","doi-asserted-by":"publisher","first-page":"602","DOI":"10.1109\/TEVC.2013.2281534","volume":"18","author":"H Jain","year":"2013","unstructured":"Jain, H., Deb, K.: An evolutionary many-objective optimization algorithm using reference-point based non-dominated sorting approach, part II: handling constraints and extending to an adaptive approach. IEEE Trans. Evol. Comput.Evol. Comput. 18(4), 602\u2013622 (2013)","journal-title":"IEEE Trans. Evol. Comput.Evol. Comput."},{"issue":"6","key":"722_CR55","doi-asserted-by":"publisher","first-page":"838","DOI":"10.1109\/TEVC.2015.2395073","volume":"19","author":"R Cheng","year":"2015","unstructured":"Cheng, R., Jin, Y., Narukawa, K., et al.: A multiobjective evolutionary algorithm using Gaussian process-based inverse modeling. IEEE Trans. Evol. Comput.Evol. Comput. 19(6), 838\u2013856 (2015)","journal-title":"IEEE Trans. Evol. Comput.Evol. Comput."},{"key":"722_CR56","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1109\/MCI.2017.2742868","volume":"12","author":"Y Tian","year":"2017","unstructured":"Tian, Y., Cheng, R., Zhang, X.Y., Jin, Y.C.: PlatEMO: A Matlab platform for evolutionary multi-objective optimization. IEEE Comput. Intell. Mag.Comput. Intell. Mag. 12, 73\u201387 (2017)","journal-title":"IEEE Comput. Intell. Mag.Comput. Intell. Mag."},{"key":"722_CR57","doi-asserted-by":"publisher","unstructured":"Zhou, A.M., Jin, Y.C., Zhang, Q.F., Sendhoff, B., Tsang, E.: Combining model-based and genetics-based offspring generation for multi-objective optimization using a convergence criterion. In: 2006 IEEE Int Conf Evol Comput, pp. 892\u2013899. https:\/\/doi.org\/10.1109\/CEC.2006.1688406 (2006)","DOI":"10.1109\/CEC.2006.1688406"},{"issue":"1","key":"722_CR58","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1109\/TEVC.2005.851275","volume":"10","author":"L While","year":"2006","unstructured":"While, L., Hingston, P., Barone, L., Huband, S.: A faster algorithm for calculating hypervolume. IEEE Trans. Evol. Comput.Evol. Comput. 10(1), 29\u201338 (2006). https:\/\/doi.org\/10.1109\/TEVC.2005.851275","journal-title":"IEEE Trans. Evol. Comput.Evol. Comput."}],"container-title":["International Journal of Computational Intelligence Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s44196-024-00722-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s44196-024-00722-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s44196-024-00722-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,8]],"date-time":"2025-01-08T17:02:12Z","timestamp":1736355732000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s44196-024-00722-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1,8]]},"references-count":58,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["722"],"URL":"https:\/\/doi.org\/10.1007\/s44196-024-00722-2","relation":{},"ISSN":["1875-6883"],"issn-type":[{"value":"1875-6883","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,1,8]]},"assertion":[{"value":"4 September 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 December 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 January 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors certify that they have no competing financial interests or personal relationships that could have influenced the work presented in this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"2"}}