{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,27]],"date-time":"2026-05-27T21:09:34Z","timestamp":1779916174578,"version":"3.53.1"},"reference-count":30,"publisher":"Springer Science and Business Media LLC","issue":"20","license":[{"start":{"date-parts":[[2017,12,16]],"date-time":"2017-12-16T00:00:00Z","timestamp":1513382400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"name":"National Natural Science Foundation of China (CN)","award":["61571346"],"award-info":[{"award-number":["61571346"]}]},{"name":"National Natural Science Foundation of China (CN)","award":["61305041"],"award-info":[{"award-number":["61305041"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61305040"],"award-info":[{"award-number":["61305040"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Soft Comput"],"published-print":{"date-parts":[[2018,10]]},"DOI":"10.1007\/s00500-017-2980-1","type":"journal-article","created":{"date-parts":[[2017,12,16]],"date-time":"2017-12-16T00:14:01Z","timestamp":1513383241000},"page":"6845-6859","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Distance-dependent parameter adaption for multi-objective evolutionary algorithm based on decomposition"],"prefix":"10.1007","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1677-2107","authenticated-orcid":false,"given":"Weikang","family":"Ning","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Baolong","family":"Guo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yunyi","family":"Yan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jie","family":"Hou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2017,12,16]]},"reference":[{"issue":"2","key":"2980_CR1","doi-asserted-by":"publisher","first-page":"174","DOI":"10.1109\/TEVC.2003.810761","volume":"7","author":"PAN Bosman","year":"2003","unstructured":"Bosman PAN, Thierens D (2003) The balance between proximity and diversity in multiobjective evolutionary algorithms. IEEE Trans Evol Comput 7(2):174\u2013188. https:\/\/doi.org\/10.1109\/TEVC.2003.810761","journal-title":"IEEE Trans Evol Comput"},{"key":"2980_CR2","doi-asserted-by":"publisher","unstructured":"Bradstreet L, Barone L, While L, Huband S, Hingston P (2007) Use of the WFG toolkit and PISA for comparison of MOEAs. ECU Publications Pre 2011. https:\/\/doi.org\/10.1109\/MCDM.2007.369117","DOI":"10.1109\/MCDM.2007.369117"},{"issue":"6","key":"2980_CR3","doi-asserted-by":"publisher","first-page":"646","DOI":"10.1109\/TEVC.2006.872133","volume":"10","author":"J Brest","year":"2006","unstructured":"Brest J, Greiner S, Boskovic B, Mernik M, Zumer V (2006) Self-adapting control parameters in differential evolution: a comparative study on numerical benchmark problems. IEEE Trans Evol Comput 10(6):646\u2013657. https:\/\/doi.org\/10.1109\/TEVC.2006.872133","journal-title":"IEEE Trans Evol Comput"},{"issue":"1","key":"2980_CR4","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1109\/TEVC.2010.2059031","volume":"15","author":"S Das","year":"2011","unstructured":"Das S, Suganthan P (2011) Differential evolution: a survey of the state-of-the-art. IEEE Trans Evol Comput 15(1):4\u201331. https:\/\/doi.org\/10.1109\/TEVC.2010.2059031","journal-title":"IEEE Trans Evol Comput"},{"key":"2980_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.swevo.2016.01.004","volume":"27","author":"S Das","year":"2016","unstructured":"Das S, Mullick SS, Suganthan PN (2016) Recent advances in differential evolution\u2014an updated survey. Swarm Evol Comput 27:1\u201330. https:\/\/doi.org\/10.1016\/j.swevo.2016.01.004","journal-title":"Swarm Evol Comput"},{"key":"2980_CR6","doi-asserted-by":"publisher","unstructured":"Durillo JJ, Nebro AJ, Alba E (2010) The jMetal framework for multi-objective optimization: design and architecture. In: IEEE congress on evolutionary computation, pp 1\u20138. https:\/\/doi.org\/10.1109\/CEC.2010.5586354","DOI":"10.1109\/CEC.2010.5586354"},{"issue":"18","key":"2980_CR7","doi-asserted-by":"publisher","first-page":"3749","DOI":"10.1016\/j.ins.2011.03.010","volume":"181","author":"A Ghosh","year":"2011","unstructured":"Ghosh A, Das S, Chowdhury A, Giri R (2011) An improved differential evolution algorithm with fitness-based adaptation of the control parameters. Inf Sci 181(18):3749\u20133765. https:\/\/doi.org\/10.1016\/j.ins.2011.03.010","journal-title":"Inf Sci"},{"key":"2980_CR8","doi-asserted-by":"publisher","unstructured":"Ishibuchi H, Tanigaki Y, Masuda H, Nojima Y (2014) Distance-based analysis of crossover operators for many-objective knapsack problems. In: Parallel problem solving from nature\u2014PPSN XIII, No. 8672 in lecture notes in computer science. Springer, pp 600\u2013610. https:\/\/doi.org\/10.1007\/978-3-319-10762-2_59","DOI":"10.1007\/978-3-319-10762-2_59"},{"issue":"2","key":"2980_CR9","doi-asserted-by":"publisher","first-page":"167","DOI":"10.1109\/TEVC.2014.2308294","volume":"19","author":"G Karafotias","year":"2015","unstructured":"Karafotias G, Hoogendoorn M, Eiben A (2015) Parameter control in evolutionary algorithms: trends and challenges. IEEE Trans Evol Comput 19(2):167\u2013187. https:\/\/doi.org\/10.1109\/TEVC.2014.2308294","journal-title":"IEEE Trans Evol Comput"},{"issue":"2","key":"2980_CR10","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 Trans Evol Comput 13(2):284\u2013302","journal-title":"IEEE Trans Evol Comput"},{"key":"2980_CR11","doi-asserted-by":"crossref","unstructured":"Li K, Fialho \u00c1, Kwong S (2011) Multi-objective differential evolution with adaptive control of parameters and operators. In: International conference on learning and intelligent optimization, Springer, pp 473\u2013487","DOI":"10.1007\/978-3-642-25566-3_37"},{"issue":"1","key":"2980_CR12","doi-asserted-by":"publisher","first-page":"114","DOI":"10.1109\/TEVC.2013.2239648","volume":"18","author":"K Li","year":"2014","unstructured":"Li K, Fialho A, Kwong S, Zhang Q (2014a) Adaptive operator selection with bandits for a multiobjective evolutionary algorithm based on decomposition. IEEE Trans Evol Comput 18(1):114\u2013130. https:\/\/doi.org\/10.1109\/TEVC.2013.2239648","journal-title":"IEEE Trans Evol Comput"},{"issue":"6","key":"2980_CR13","doi-asserted-by":"crossref","first-page":"909","DOI":"10.1109\/TEVC.2013.2293776","volume":"18","author":"K Li","year":"2014","unstructured":"Li K, Zhang Q, Kwong S, Li M, Wang R (2014b) Stable matching-based selection in evolutionary multiobjective optimization. IEEE Trans Evol Comput 18(6):909\u2013923","journal-title":"IEEE Trans Evol Comput"},{"issue":"10","key":"2980_CR14","first-page":"2076","volume":"45","author":"K Li","year":"2015","unstructured":"Li K, Kwong S, Zhang Q, Deb K (2015) Interrelationship-based selection for decomposition multiobjective optimization. IEEE Trans Syst Man Cybern 45(10):2076\u20132088","journal-title":"IEEE Trans Syst Man Cybern"},{"key":"2980_CR15","doi-asserted-by":"publisher","first-page":"332","DOI":"10.1016\/j.ins.2015.12.022","volume":"339","author":"Q Lin","year":"2016","unstructured":"Lin Q, Liu Z, Yan Q, Du Z, Coello CAC, Liang Z, Wang W, Chen J (2016) Adaptive composite operator selection and parameter control for multiobjective evolutionary algorithm. Inf Sci 339:332\u2013352. https:\/\/doi.org\/10.1016\/j.ins.2015.12.022","journal-title":"Inf Sci"},{"issue":"3","key":"2980_CR16","doi-asserted-by":"crossref","first-page":"450","DOI":"10.1109\/TEVC.2013.2281533","volume":"18","author":"HL Liu","year":"2014","unstructured":"Liu HL, Gu F, Zhang Q (2014) Decomposition of a multiobjective optimization problem into a number of simple multiobjective subproblems. IEEE Trans Evol Comput 18(3):450\u2013455","journal-title":"IEEE Trans Evol Comput"},{"issue":"2","key":"2980_CR17","doi-asserted-by":"publisher","first-page":"398","DOI":"10.1109\/TEVC.2008.927706","volume":"13","author":"AK Qin","year":"2009","unstructured":"Qin AK, Huang VL, Suganthan PN (2009) Differential evolution algorithm with strategy adaptation for global numerical optimization. IEEE Trans Evol Comput 13(2):398\u2013417. https:\/\/doi.org\/10.1109\/TEVC.2008.927706","journal-title":"IEEE Trans Evol Comput"},{"key":"2980_CR18","doi-asserted-by":"publisher","unstructured":"Qiu X, Xu W, Xu JX, Tan KC (2015) A new framework for self-adapting control parameters in multi-objective optimization. In: Proceedings of the 2015 annual conference on genetic and evolutionary computation, ACM, New York, NY, USA, GECCO \u201915, pp 743\u2013750. https:\/\/doi.org\/10.1145\/2739480.2754714","DOI":"10.1145\/2739480.2754714"},{"issue":"2","key":"2980_CR19","doi-asserted-by":"crossref","first-page":"232","DOI":"10.1109\/TEVC.2015.2433672","volume":"20","author":"X Qiu","year":"2016","unstructured":"Qiu X, Xu J, Tan KC, Abbass HA (2016) Adaptive cross-generation differential evolution operators for multiobjective optimization. IEEE Trans Evol Comput 20(2):232\u2013244","journal-title":"IEEE Trans Evol Comput"},{"issue":"2","key":"2980_CR20","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1007\/s005000050009","volume":"1","author":"JE Smith","year":"1997","unstructured":"Smith JE, Fogarty TC (1997) Operator and parameter adaptation in genetic algorithms. Soft Comput 1(2):81\u201387. https:\/\/doi.org\/10.1007\/s005000050009","journal-title":"Soft Comput"},{"issue":"1","key":"2980_CR21","first-page":"341","volume":"23","author":"R Storn","year":"1995","unstructured":"Storn R, Price K (1995) Differential evolution: a simple and efficient adaptive scheme for global optimization over continuous spaces. J Glob Optim 23(1):341\u2013359","journal-title":"J Glob Optim"},{"issue":"1","key":"2980_CR22","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1109\/TEVC.2010.2087271","volume":"15","author":"Y Wang","year":"2011","unstructured":"Wang Y, Cai Z, Zhang Q (2011) Differential evolution with composite trial vector generation strategies and control parameters. IEEE Trans Evol Comput 15(1):55\u201366. https:\/\/doi.org\/10.1109\/TEVC.2010.2087271","journal-title":"IEEE Trans Evol Comput"},{"issue":"6","key":"2980_CR23","doi-asserted-by":"publisher","first-page":"712","DOI":"10.1109\/TEVC.2007.892759","volume":"11","author":"Q Zhang","year":"2007","unstructured":"Zhang Q, Li H (2007) MOEA\/D: a multiobjective evolutionary algorithm based on decomposition. IEEE Trans Evol Comput 11(6):712\u2013731. https:\/\/doi.org\/10.1109\/TEVC.2007.892759","journal-title":"IEEE Trans Evol Comput"},{"issue":"5","key":"2980_CR24","doi-asserted-by":"publisher","first-page":"945","DOI":"10.1109\/TEVC.2009.2014613","volume":"13","author":"J Zhang","year":"2009","unstructured":"Zhang J, Sanderson AC (2009) JADE: adaptive differential evolution with optional external archive. IEEE Trans Evol Comput 13(5):945\u2013958. https:\/\/doi.org\/10.1109\/TEVC.2009.2014613","journal-title":"IEEE Trans Evol Comput"},{"key":"2980_CR25","unstructured":"Zhang Q, Zhou A, Zhao S, Suganthan PN, Liu W, Tiwari S (2008) Multiobjective optimization test instances for the CEC 2009 special session and competition. University of Essex, Colchester, UK and Nanyang Technological University, Singapore, Special session on performance assessment of multi-objective optimization algorithms, technical report"},{"key":"2980_CR26","doi-asserted-by":"publisher","unstructured":"Zhang Q, Liu W, Li H (2009) The performance of a new version of MOEA\/D on CEC09 unconstrained MOP test instances. In: IEEE congress on evolutionary computation, 2009. CEC \u201909, pp 203\u2013208. https:\/\/doi.org\/10.1109\/CEC.2009.4982949","DOI":"10.1109\/CEC.2009.4982949"},{"key":"2980_CR27","doi-asserted-by":"publisher","unstructured":"Zhang SX, Zheng LM, Liu L, Zheng SY, Pan YM (2016) Decomposition-based multi-objective evolutionary algorithm with mating neighborhood sizes and reproduction operators adaptation. Soft Comput 1\u201312, https:\/\/doi.org\/10.1007\/s00500-016-2196-9","DOI":"10.1007\/s00500-016-2196-9"},{"issue":"3","key":"2980_CR28","doi-asserted-by":"publisher","first-page":"442","DOI":"10.1109\/TEVC.2011.2166159","volume":"16","author":"SZ Zhao","year":"2012","unstructured":"Zhao SZ, Suganthan P, Zhang Q (2012) Decomposition-based multiobjective evolutionary algorithm with an ensemble of neighborhood sizes. IEEE Trans Evol Comput 16(3):442\u2013446. https:\/\/doi.org\/10.1109\/TEVC.2011.2166159","journal-title":"IEEE Trans Evol Comput"},{"issue":"1","key":"2980_CR29","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1109\/TEVC.2015.2424251","volume":"20","author":"A Zhou","year":"2016","unstructured":"Zhou A, Zhang Q (2016) Are all the subproblems equally important? Resource allocation in decomposition-based multiobjective evolutionary algorithms. IEEE Trans Evol Comput 20(1):52\u201364","journal-title":"IEEE Trans Evol Comput"},{"issue":"4","key":"2980_CR30","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1109\/4235.797969","volume":"3","author":"E Zitzler","year":"1999","unstructured":"Zitzler E, Thiele L (1999) Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach. IEEE Trans Evol Comput 3(4):257\u2013271. https:\/\/doi.org\/10.1109\/4235.797969","journal-title":"IEEE Trans Evol Comput"}],"container-title":["Soft Computing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00500-017-2980-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00500-017-2980-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00500-017-2980-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,10,7]],"date-time":"2019-10-07T23:38:57Z","timestamp":1570491537000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00500-017-2980-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,12,16]]},"references-count":30,"journal-issue":{"issue":"20","published-print":{"date-parts":[[2018,10]]}},"alternative-id":["2980"],"URL":"https:\/\/doi.org\/10.1007\/s00500-017-2980-1","relation":{},"ISSN":["1432-7643","1433-7479"],"issn-type":[{"value":"1432-7643","type":"print"},{"value":"1433-7479","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,12,16]]}}}