{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T09:28:00Z","timestamp":1758274080901,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":21,"publisher":"Springer Singapore","isbn-type":[{"type":"print","value":"9789811912559"},{"type":"electronic","value":"9789811912566"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"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":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-981-19-1256-6_11","type":"book-chapter","created":{"date-parts":[[2022,3,23]],"date-time":"2022-03-23T15:02:59Z","timestamp":1648047779000},"page":"145-159","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A Differential Evolution Algorithm for Multi-objective Mixed-Variable Optimization Problems"],"prefix":"10.1007","author":[{"given":"Yupeng","family":"Han","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hu","family":"Peng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aiwen","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cong","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fanrong","family":"Kong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mengmeng","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,3,24]]},"reference":[{"issue":"3","key":"11_CR1","doi-asserted-by":"publisher","first-page":"471","DOI":"10.1007\/s00158-015-1319-8","volume":"53","author":"W Tong","year":"2015","unstructured":"Tong, W., Chowdhury, S., Messac, A.: A multi-objective mixed-discrete particle swarm optimization with multi-domain diversity preservation. Struct. Multidiscip. Optim. 53(3), 471\u2013488 (2015). https:\/\/doi.org\/10.1007\/s00158-015-1319-8","journal-title":"Struct. Multidiscip. Optim."},{"key":"11_CR2","doi-asserted-by":"publisher","first-page":"107366","DOI":"10.1016\/j.knosys.2021.107366","volume":"229","author":"H Peng","year":"2021","unstructured":"Peng, H., Han, Y., Deng, C., Wang, J., Wu, Z.: Multi-strategy co-evolutionary differential evolution for mixed-variable optimization. Knowl.-Based Syst. 229, 107366 (2021)","journal-title":"Knowl.-Based Syst."},{"key":"11_CR3","doi-asserted-by":"publisher","first-page":"107403","DOI":"10.1016\/j.asoc.2021.107403","volume":"108","author":"AM Altabeeb","year":"2021","unstructured":"Altabeeb, A.M., Mohsen, A.M., Abualigah, L., Ghallab, A.: Solving capacitated vehicle routing problem using cooperative firefly algorithm. Appl. Soft Comput. 108, 107403 (2021)","journal-title":"Appl. Soft Comput."},{"key":"11_CR4","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1016\/j.knosys.2016.08.007","volume":"111","author":"L Cui","year":"2016","unstructured":"Cui, L., Deng, J., Wang, L., Xu, M., Zhang, Y.: A novel locust swarm algorithm for the joint replenishment problem considering multiple discounts simultaneously. Knowl-Based Syst. 111, 51\u201362 (2016)","journal-title":"Knowl-Based Syst."},{"key":"11_CR5","doi-asserted-by":"publisher","first-page":"108139","DOI":"10.1016\/j.ijpe.2021.108139","volume":"237","author":"M Fathi","year":"2021","unstructured":"Fathi, M., Khakifirooz, M., Diabat, A., Chen, H.: An integrated queuing stochastic optimization hybrid Genetic Algorithm for a location-inventory supply chain network. Int. J. Prod. Econ. 237, 108139 (2021)","journal-title":"Int. J. Prod. Econ."},{"issue":"2","key":"11_CR6","doi-asserted-by":"publisher","first-page":"182","DOI":"10.1109\/4235.996017","volume":"6","author":"K Deb","year":"2002","unstructured":"Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans. Evol. Comput. 6(2), 182\u2013197 (2002)","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"6","key":"11_CR7","doi-asserted-by":"publisher","first-page":"712","DOI":"10.1109\/TEVC.2007.892759","volume":"11","author":"Q Zhang","year":"2008","unstructured":"Zhang, Q., Hui, L.: Moea\/d: A multiobjective evolutionary algorithm based on decomposition. IEEE Trans. Evol. Comput. 11(6), 712\u2013731 (2008)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"11_CR8","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"832","DOI":"10.1007\/978-3-540-30217-9_84","volume-title":"Parallel Problem Solving from Nature - PPSN VIII","author":"E Zitzler","year":"2004","unstructured":"Zitzler, E., K\u00fcnzli, S.: Indicator-based selection in multiobjective search. In: Yao, X., et al. (eds.) PPSN 2004. LNCS, vol. 3242, pp. 832\u2013842. Springer, Heidelberg (2004). https:\/\/doi.org\/10.1007\/978-3-540-30217-9_84"},{"issue":"4","key":"11_CR9","doi-asserted-by":"publisher","first-page":"341","DOI":"10.1023\/A:1008202821328","volume":"11","author":"R Storn","year":"1997","unstructured":"Storn, R., Price, K.: Differential evolution\u2013a simple and efficient heuristic for global optimization over continuous spaces. J. Global Optim. 11(4), 341\u2013359 (1997)","journal-title":"J. Global Optim."},{"issue":"2","key":"11_CR10","doi-asserted-by":"publisher","first-page":"284","DOI":"10.1109\/TEVC.2008.925798","volume":"13","author":"H Li","year":"2008","unstructured":"Li, H., Zhang, Q.: Multiobjective optimization problems with complicated Pareto sets, MOEA\/D and NSGA-II. IEEE Trans. Evol. Comput. 13(2), 284\u2013302 (2008)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"11_CR11","doi-asserted-by":"publisher","first-page":"501","DOI":"10.1016\/j.jocs.2017.07.010","volume":"26","author":"H Peng","year":"2018","unstructured":"Peng, H., Guo, Z., Deng, C., Wu, Z.: Enhancing differential evolution with random neighbors based strategy. J. Comput. Sci. 26, 501\u2013511 (2018)","journal-title":"J. Comput. Sci."},{"issue":"4","key":"11_CR12","doi-asserted-by":"publisher","first-page":"995","DOI":"10.1109\/TCYB.2016.2536167","volume":"47","author":"X Qiu","year":"2016","unstructured":"Qiu, X., Tan, K.C., Xu, J.: Multiple exponential recombination for differential evolution. IEEE Trans. Cybernet. 47(4), 995\u20131006 (2016)","journal-title":"IEEE Trans. Cybernet."},{"issue":"4","key":"11_CR13","doi-asserted-by":"publisher","first-page":"503","DOI":"10.1109\/TEVC.2013.2281531","volume":"18","author":"T Liao","year":"2013","unstructured":"Liao, T., Socha, K., de Oca, M.A.M., St\u00fctzle, T., Dorigo, M.: Ant colony optimization for mixed-variable optimization problems. IEEE Trans. Evol. Comput. 18(4), 503\u2013518 (2013)","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"2\u20134","key":"11_CR14","doi-asserted-by":"publisher","first-page":"311","DOI":"10.1016\/S0045-7825(99)00389-8","volume":"186","author":"K Deb","year":"2000","unstructured":"Deb, K.: An efficient constraint handling method for genetic algorithms. Comput. Meth. Appl. Mech. Eng. 186(2\u20134), 311\u2013338 (2000)","journal-title":"Comput. Meth. Appl. Mech. Eng."},{"issue":"4","key":"11_CR15","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., Jin, Y.: PlatEMO: A MATLAB platform for evolutionary multi-objective optimization [educational forum]. IEEE Comput. Intell. Mag. 12(4), 73\u201387 (2017)","journal-title":"IEEE Comput. Intell. Mag."},{"issue":"6","key":"11_CR16","doi-asserted-by":"publisher","first-page":"1510","DOI":"10.1109\/TCYB.2016.2550502","volume":"47","author":"H Wang","year":"2017","unstructured":"Wang, H., Jin, Y., Yao, X.: Diversity assessment in many-objective optimization. IEEE Trans. Cybernet. 47(6), 1510\u20131522 (2017)","journal-title":"IEEE Trans. Cybernet."},{"issue":"4","key":"11_CR17","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. 18(4), 602\u2013622 (2013)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"11_CR18","doi-asserted-by":"publisher","first-page":"S951","DOI":"10.1016\/S0098-1354(98)00188-4","volume":"22","author":"TI Dimkou","year":"1998","unstructured":"Dimkou, T.I., Papalexandri, K.P.: A parametric optimization approach for multiobjective engineering problems involving discrete decisions. Comput. Chem. Eng. 22, S951\u2013S954 (1998)","journal-title":"Comput. Chem. Eng."},{"key":"11_CR19","unstructured":"Osyczka, A., Kundu, S.: A genetic algorithm-based multicriteria optimization method. In: Proceedings of the 1st World Congress of Structural Multidisciplinary Optimization, pp. 909\u2013914 1995)"},{"issue":"7","key":"11_CR20","doi-asserted-by":"publisher","first-page":"071009","DOI":"10.1115\/1.4001599","volume":"132","author":"ZO Khokhar","year":"2010","unstructured":"Khokhar, Z.O., et al.: \u201cOn the performance of the PSP method for mixed-variable multi-objective design optimization. J. Mech. Des. 132(7), 071009 (2010)","journal-title":"J. Mech. Des."},{"key":"11_CR21","doi-asserted-by":"publisher","first-page":"100928","DOI":"10.1016\/j.swevo.2021.100928","volume":"66","author":"Y Chen","year":"2021","unstructured":"Chen, Y., Zhou, A., Das, S.: utilizing dependence among variables in evolutionary algorithms for mixed-integer programming: a case study on multi-objective constrained portfolio optimization. Swarm Evol. Comput. 66, 100928 (2021)","journal-title":"Swarm Evol. Comput."}],"container-title":["Communications in Computer and Information Science","Bio-Inspired Computing: Theories and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-19-1256-6_11","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,3,23]],"date-time":"2022-03-23T15:03:57Z","timestamp":1648047837000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-19-1256-6_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9789811912559","9789811912566"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-981-19-1256-6_11","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"24 March 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"BIC-TA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Bio-Inspired Computing: Theories and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Taiyuan","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 December 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 December 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"bicta2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/2021.bicta.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"211","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"67","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"32% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}