{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T16:11:50Z","timestamp":1778861510004,"version":"3.51.4"},"reference-count":40,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2020,1,22]],"date-time":"2020-01-22T00:00:00Z","timestamp":1579651200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,22]],"date-time":"2020-01-22T00:00:00Z","timestamp":1579651200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Wireless Netw"],"published-print":{"date-parts":[[2021,7]]},"DOI":"10.1007\/s11276-019-02228-8","type":"journal-article","created":{"date-parts":[[2020,1,22]],"date-time":"2020-01-22T17:03:02Z","timestamp":1579712582000},"page":"3573-3583","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["A knee point-driven multi-objective artificial flora optimization algorithm"],"prefix":"10.1007","volume":"27","author":[{"given":"Xuehan","family":"Wu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shafei","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ye","family":"Pan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huaizong","family":"Shao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,1,22]]},"reference":[{"issue":"10","key":"2228_CR1","doi-asserted-by":"crossref","first-page":"3305","DOI":"10.1109\/TITS.2017.2778939","volume":"99","author":"D Jiang","year":"2018","unstructured":"Jiang, D., Huo, L., Lv, Z., Song, H., & Qin, W. (2018). A joint multi-criteria utility-based network selection approach for vehicle-to-infrastructure networking. IEEE Transactions on Intelligent Transportation Systems, 99(10), 3305\u20133319.","journal-title":"IEEE Transactions on Intelligent Transportation Systems"},{"key":"2228_CR2","doi-asserted-by":"crossref","first-page":"22013","DOI":"10.1109\/ACCESS.2017.2760885","volume":"5","author":"M Sun","year":"2017","unstructured":"Sun, M., Jiang, D., Song, H., & Liu, Y. (2017). Statistical resolution limit analysis of two closely spaced signal sources using rao test. IEEE Access, 5, 22013\u201322020.","journal-title":"IEEE Access"},{"issue":"1","key":"2228_CR3","doi-asserted-by":"crossref","first-page":"438","DOI":"10.1016\/j.advwatres.2012.01.005","volume":"51","author":"PM Reed","year":"2013","unstructured":"Reed, P. M., Hadka, D., Herman, J. D., Kasprzyk, J. R., & Kollat, J. B. (2013). Evolutionary multiobjective optimization in water resources: The past, present, and future. Advances in Water Resources, 51(1), 438\u2013456.","journal-title":"Advances in Water Resources"},{"issue":"8","key":"2228_CR4","doi-asserted-by":"crossref","first-page":"5511","DOI":"10.1109\/TWC.2016.2560815","volume":"15","author":"DWK Ng","year":"2016","unstructured":"Ng, D. W. K., Yan, S., & Schober, R. (2016). Power efficient and secure full-duplex wireless communication systems. IEEE Transactions on Wireless Communications, 15(8), 5511\u20135526.","journal-title":"IEEE Transactions on Wireless Communications"},{"issue":"3","key":"2228_CR5","doi-asserted-by":"crossref","first-page":"314","DOI":"10.1016\/j.ress.2006.04.014","volume":"92","author":"HA Taboada","year":"2007","unstructured":"Taboada, H. A., Baheranwala, F., Coit, D. W., & Wattanapongsakorn, N. (2007). Practical solutions for multi-objective optimization: An application to system reliability design problems. Reliability Engineering and System Safety, 92(3), 314\u2013322.","journal-title":"Reliability Engineering and System Safety"},{"issue":"1","key":"2228_CR6","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1109\/TPWRS.2005.860946","volume":"21","author":"IJ Ramirez-Rosado","year":"2006","unstructured":"Ramirez-Rosado, I. J., & Dominguez-Navarro, J. A. (2006). New multiobjective tabu search algorithm for fuzzy optimal planning of power distribution systems. IEEE Transactions on Power Systems, 21(1), 224\u2013233.","journal-title":"IEEE Transactions on Power Systems"},{"issue":"3","key":"2228_CR7","first-page":"1","volume":"5","author":"D Jiang","year":"2018","unstructured":"Jiang, D., Wang, W., Shi, L., & Song, H. (2018). A compressive sensing-based approach to end-to-end network traffic reconstruction. IEEE Transactions on Network Science and Engineering, 5(3), 1\u201312.","journal-title":"IEEE Transactions on Network Science and Engineering"},{"issue":"2","key":"2228_CR8","doi-asserted-by":"crossref","first-page":"284","DOI":"10.1109\/TEVC.2008.925798","volume":"13","author":"H Li","year":"2009","unstructured":"Li, H., & Zhang, Q. (2009). Multiobjective optimization problems with complicated pareto sets, MOEA\/D and NSGA-II. IEEE Transactions on Evolutionary Computation, 13(2), 284\u2013302.","journal-title":"IEEE Transactions on Evolutionary Computation"},{"issue":"3","key":"2228_CR9","doi-asserted-by":"crossref","first-page":"1401","DOI":"10.1109\/TSG.2015.2468683","volume":"7","author":"A Asrari","year":"2016","unstructured":"Asrari, A., Lotfifard, S., & Payam, M. S. (2016). Pareto dominance-based multiobjective optimization method for distribution network reconfiguration. IEEE Transactions on Smart Grid, 7(3), 1401\u20131410.","journal-title":"IEEE Transactions on Smart Grid"},{"issue":"1","key":"2228_CR10","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1109\/MCI.2006.1597059","volume":"1","author":"CAC Coello","year":"2006","unstructured":"Coello, C. A. C. (2006). Evolutionary multi-objective optimization: A historical view of the field. IEEE Computational Intelligence Magazine, 1(1), 28\u201336.","journal-title":"IEEE Computational Intelligence Magazine"},{"issue":"2","key":"2228_CR11","doi-asserted-by":"crossref","first-page":"316","DOI":"10.1016\/j.compeleceng.2017.09.009","volume":"66","author":"L Huo","year":"2018","unstructured":"Huo, L., Jiang, D., Lv, Z., Huo, L., Jiang, D., Lv, Z., et al. (2018). Soft frequency reuse-based optimization algorithm for energy efficiency of multi-cell networks. Computers and Electrical Engineering, 66(2), 316\u2013331.","journal-title":"Computers and Electrical Engineering"},{"issue":"9","key":"2228_CR12","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TCYB.2017.2716519","volume":"47","author":"B Ji","year":"2017","unstructured":"Ji, B., Yuan, X., & Yuan, Y. (2017). Modified NSGA-II for solving continuous berth allocation problem: Using multiobjective constraint-handling strategy. IEEE Transactions on Cybernetics, 47(9), 1\u201311.","journal-title":"IEEE Transactions on Cybernetics"},{"issue":"1","key":"2228_CR13","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.swevo.2011.08.001","volume":"2","author":"R Akbari","year":"2012","unstructured":"Akbari, R., Hedayatzadeh, R., Ziarati, K., & Hassanizadeh, B. (2012). A multi-objective artificial bee colony algorithm. Swarm and Evolutionary Computation, 2(1), 39\u201352.","journal-title":"Swarm and Evolutionary Computation"},{"key":"2228_CR14","doi-asserted-by":"crossref","unstructured":"Mirjalili, S. Z., Mirjalili, S., Saremi, S., Faris, H., & Aljarah, I. (2017). Grasshopper optimization algorithm for multi-objective optimization problems. Applied Intelligence, 1\u201316.","DOI":"10.1007\/s10489-017-1019-8"},{"key":"2228_CR15","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1016\/j.ins.2016.08.043","volume":"375","author":"L Li","year":"2017","unstructured":"Li, L., Wang, W., & Xu, X. (2017). Multi-objective particle swarm optimization based on global margin ranking. Information Sciences, 375, 30\u201347.","journal-title":"Information Sciences"},{"issue":"3","key":"2228_CR16","doi-asserted-by":"crossref","first-page":"329","DOI":"10.3390\/app8030329","volume":"8","author":"L Cheng","year":"2018","unstructured":"Cheng, L., Wu, X., & Wang, Y. (2018). Artificial flora (AF) optimization algorithm. Applied Sciences, 8(3), 329\u201352.","journal-title":"Applied Sciences"},{"key":"2228_CR17","doi-asserted-by":"crossref","unstructured":"Kong, W., Ding, J., Chai, T., & Jing, S. (2010). Large-dimensional multi-objective evolutionary algorithms based on improved average ranking. In IEEE conference on decision and control.","DOI":"10.1109\/CDC.2010.5716986"},{"issue":"6","key":"2228_CR18","doi-asserted-by":"crossref","first-page":"1437","DOI":"10.1109\/JIOT.2016.2613111","volume":"3","author":"D Jiang","year":"2016","unstructured":"Jiang, D., Zhang, P., Lv, Z., & Song, H. (2016). Energy-efficient multi-constraint routing algorithm with load balancing for smart city applications. IEEE Internet of Things Journal, 3(6), 1437\u20131447.","journal-title":"IEEE Internet of Things Journal"},{"issue":"5","key":"2228_CR19","doi-asserted-by":"crossref","first-page":"801","DOI":"10.1109\/TEVC.2010.2041060","volume":"14","author":"LB Said","year":"2010","unstructured":"Said, L. B., Bechikh, S., & Ghedira, K. (2010). The r-dominance: A new dominance relation for interactive evolutionary multicriteria decision making. IEEE Transactions on Evolutionary Computation, 14(5), 801\u2013818.","journal-title":"IEEE Transactions on Evolutionary Computation"},{"issue":"4","key":"2228_CR20","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/03772063.2017.1284618","volume":"63","author":"M Ojha","year":"2017","unstructured":"Ojha, M., Singh, K. P., Chakraborty, P., Verma, S., & Pandey, P. S. (2017). An empirical study of aggregation operators with pareto dominance in multiobjective genetic algorithm. IETE Journal of Research, 63(4), 1\u201311.","journal-title":"IETE Journal of Research"},{"issue":"4","key":"2228_CR21","doi-asserted-by":"crossref","first-page":"879","DOI":"10.1016\/j.cma.2006.07.010","volume":"196","author":"T Goel","year":"2007","unstructured":"Goel, T., Vaidyanathan, R., Haftka, R. T., Wei, S., Queipo, N. V., & Tucker, K. (2007). Response surface approximation of pareto optimal front in multi-objective optimization. Computer Methods in Applied Mechanics and Engineering, 196(4), 879\u2013893.","journal-title":"Computer Methods in Applied Mechanics and Engineering"},{"issue":"3","key":"2228_CR22","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1162\/106365602760234108","volume":"10","author":"M Laumanns","year":"2002","unstructured":"Laumanns, M., Thiele, L., Deb, K., & Zitzler, E. (2002). Combining convergence and diversity in evolutionary multiobjective optimization. Evolutionary Computation, 10(3), 263\u2013282.","journal-title":"Evolutionary Computation"},{"key":"2228_CR23","doi-asserted-by":"crossref","first-page":"15408","DOI":"10.1109\/ACCESS.2018.2794354","volume":"6","author":"C Lei","year":"2018","unstructured":"Lei, C., Jiang, D., Song, H., Ping, W., Rong, B., Zhang, K., et al. (2018). A lightweight end-side user experience data collection system for quality evaluation of multimedia communications. IEEE Access, 6, 15408\u201315419.","journal-title":"IEEE Access"},{"key":"2228_CR24","doi-asserted-by":"crossref","unstructured":"Wei, J., & Wang, Y. (2006). A novel multi-objective PSO algorithm for constrained optimization problems. In International conference on simulated evolution and learning.","DOI":"10.1007\/11903697_23"},{"issue":"5","key":"2228_CR25","doi-asserted-by":"crossref","first-page":"1270","DOI":"10.1109\/TSMCB.2008.925757","volume":"38","author":"L Wen-Fung","year":"2008","unstructured":"Wen-Fung, L., & Yen, G. G. (2008). Pso-based multiobjective optimization with dynamic population size and adaptive local archives. IEEE Transactions on Systems Man and Cybernetics Part B, 38(5), 1270\u20131293.","journal-title":"IEEE Transactions on Systems Man and Cybernetics Part B"},{"key":"2228_CR26","doi-asserted-by":"crossref","first-page":"1262","DOI":"10.1016\/j.neucom.2014.11.003","volume":"151","author":"A Karami","year":"2015","unstructured":"Karami, A., & Guerrero-Zapata, M. (2015). A hybrid multiobjective RBF-PSO method for mitigating dos attacks in named data networking. Neurocomputing, 151, 1262\u20131282.","journal-title":"Neurocomputing"},{"key":"2228_CR27","first-page":"1","volume":"5","author":"Y Hao","year":"2014","unstructured":"Hao, Y., Zhang, C., Zhang, B., Ying, G., & Liu, T. (2014). A hybrid multiobjective discrete particle swarm optimization algorithm for a SLA-aware service composition problem. Mathematical Problems in Engineering, 5, 1\u201314.","journal-title":"Mathematical Problems in Engineering"},{"key":"2228_CR28","doi-asserted-by":"crossref","unstructured":"Dey, S., Bhattacharyya, S., & Maulik, U. (2015). Quantum behaved multi-objective PSO and ACO optimization for multi-level thresholding. In International conference on computational intelligence and communication networks.","DOI":"10.1109\/CICN.2014.63"},{"issue":"2","key":"2228_CR29","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1007\/s10898-012-9993-1","volume":"57","author":"B Akay","year":"2013","unstructured":"Akay, B. (2013). Synchronous and asynchronous pareto-based multi-objective artificial bee colony algorithms. Journal of Global Optimization, 57(2), 415\u2013445.","journal-title":"Journal of Global Optimization"},{"issue":"34","key":"2228_CR30","doi-asserted-by":"crossref","first-page":"1","DOI":"10.17485\/ijst\/2016\/v9i34\/95638","volume":"9","author":"N Ranjith","year":"2016","unstructured":"Ranjith, N., & Marimuthu, A. (2016). A multi objective teacher-learning-artificial bee colony (motlabc) optimization for software requirements selection. Indian Journal of Science and Technology, 9(34), 1\u20139.","journal-title":"Indian Journal of Science and Technology"},{"issue":"5","key":"2228_CR31","doi-asserted-by":"crossref","first-page":"861","DOI":"10.1109\/TSMC.2017.2723483","volume":"49","author":"L Ma","year":"2017","unstructured":"Ma, L., Wang, X., Min, H., Lin, Z., & Chen, H. (2017). Two-level master-slave RFID networks planning via hybrid multiobjective artificial bee colony optimizer. IEEE Transactions on Systems Man and Cybernetics Systems, 49(5), 861\u2013880.","journal-title":"IEEE Transactions on Systems Man and Cybernetics Systems"},{"issue":"11","key":"2228_CR32","doi-asserted-by":"crossref","first-page":"1175","DOI":"10.1080\/0305215X.2010.548863","volume":"43","author":"K Deb","year":"2011","unstructured":"Deb, K., & Gupta, S. (2011). Understanding knee points in bicriteria problems and their implications as preferred solution principles. Engineering Optimization, 43(11), 1175\u20131204.","journal-title":"Engineering Optimization"},{"issue":"6","key":"2228_CR33","doi-asserted-by":"crossref","first-page":"761","DOI":"10.1109\/TEVC.2014.2378512","volume":"19","author":"X Zhang","year":"2015","unstructured":"Zhang, X., Tian, Y., & Jin, Y. (2015). A knee point driven evolutionary algorithm for many-objective optimization. IEEE Transactions on Evolutionary Computation, 19(6), 761\u2013776.","journal-title":"IEEE Transactions on Evolutionary Computation"},{"issue":"3","key":"2228_CR34","first-page":"49","volume":"273","author":"HL Wei","year":"2014","unstructured":"Wei, H. L., & Isa, N. A. M. (2014). An adaptive two-layer particle swarm optimization with elitist learning strategy. Information Sciences, 273(3), 49\u201372.","journal-title":"Information Sciences"},{"issue":"15","key":"2228_CR35","doi-asserted-by":"crossref","first-page":"4605","DOI":"10.1080\/00207543.2010.493534","volume":"49","author":"Q Zhu","year":"2011","unstructured":"Zhu, Q., & Zhang, J. (2011). Ant colony optimisation with elitist ant for sequencing problem in a mixed model assembly line. International Journal of Production Research, 49(15), 4605\u20134626.","journal-title":"International Journal of Production Research"},{"issue":"1","key":"2228_CR36","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1016\/j.tcs.2006.04.005","volume":"361","author":"M Toussaint","year":"2006","unstructured":"Toussaint, M. (2006). Compact representations as a search strategy: Compression edas. Theoretical Computer Science, 361(1), 57\u201371.","journal-title":"Theoretical Computer Science"},{"key":"2228_CR37","doi-asserted-by":"crossref","unstructured":"Marinakis, Y., Marinaki, M., & Matsatsinis, N. (2008). A hybrid clustering algorithm based on honey bees mating optimization and greedy randomized adaptive search procedure.","DOI":"10.1007\/978-3-540-92695-5_11"},{"issue":"11","key":"2228_CR38","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TAC.2016.2610298","volume":"61","author":"C Zhu","year":"2016","unstructured":"Zhu, C., Xu, J., Chen, C. H., Lee, L. H., & Hu, J. Q. (2016). Balancing search and estimation in random search based stochastic simulation optimization. IEEE Transactions on Automatic Control, 61(11), 1\u20131.","journal-title":"IEEE Transactions on Automatic Control"},{"issue":"C","key":"2228_CR39","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/j.ins.2015.10.010","volume":"330","author":"GQ Zeng","year":"2016","unstructured":"Zeng, G. Q., Chen, J., Li, L. M., Chen, M. R., Wu, L., Dai, Y. X., et al. (2016). An improved multi-objective population-based extremal optimization algorithm with polynomial mutation. Information Sciences, 330(C), 49\u201373.","journal-title":"Information Sciences"},{"issue":"2","key":"2228_CR40","doi-asserted-by":"crossref","first-page":"463","DOI":"10.1016\/j.ejor.2004.08.038","volume":"171","author":"KC Tan","year":"2006","unstructured":"Tan, K. C., Goh, C. K., Yang, Y. J., & Lee, T. H. (2006). Evolving better population distribution and exploration in evolutionary multi-objective optimization. European Journal of Operational Research, 171(2), 463\u2013495.","journal-title":"European Journal of Operational Research"}],"container-title":["Wireless Networks"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11276-019-02228-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11276-019-02228-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11276-019-02228-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,7,3]],"date-time":"2021-07-03T06:34:13Z","timestamp":1625294053000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11276-019-02228-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,1,22]]},"references-count":40,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2021,7]]}},"alternative-id":["2228"],"URL":"https:\/\/doi.org\/10.1007\/s11276-019-02228-8","relation":{},"ISSN":["1022-0038","1572-8196"],"issn-type":[{"value":"1022-0038","type":"print"},{"value":"1572-8196","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,1,22]]},"assertion":[{"value":"22 January 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}