{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T18:21:52Z","timestamp":1783102912790,"version":"3.54.6"},"publisher-location":"Singapore","reference-count":31,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819698042","type":"print"},{"value":"9789819698059","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-981-96-9805-9_11","type":"book-chapter","created":{"date-parts":[[2025,7,25]],"date-time":"2025-07-25T05:56:10Z","timestamp":1753422970000},"page":"127-138","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Network-Assisted Evolutionary Multitask Framework for Multi-objective Optimization Problems with Unknown Constraints"],"prefix":"10.1007","author":[{"given":"Jun","family":"Ma","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yong","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruizhao","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chunlin","family":"He","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ali Wagdy","family":"Mohamed","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mingcheng","family":"Zuo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huijun","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiangjuan","family":"Yao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,7,26]]},"reference":[{"key":"11_CR1","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2021.118130","volume":"307","author":"H Hu","year":"2022","unstructured":"Hu, H., Sun, X., Zeng, B., Gong, D., Zhang, Y.: Enhanced evolutionary multi-objective optimization-based dispatch of coal mine integrated energy system with flexible load. Appl. Energy 307, 118130 (2022)","journal-title":"Appl. Energy"},{"issue":"9","key":"11_CR2","doi-asserted-by":"publisher","first-page":"11149","DOI":"10.1109\/TII.2024.3399909","volume":"20","author":"J Ma","year":"2024","unstructured":"Ma, J., Zhang, Y., Wang, Y., Gong, D., Sun, X., Zeng, B.: A multitask multiobjective operation optimization method for coal mine integrated energy system. IEEE Trans. Ind. Informat. 20(9), 11149\u201311160 (2024)","journal-title":"IEEE Trans. Ind. Informat."},{"key":"11_CR3","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2021.116759","volume":"290","author":"H Huang","year":"2021","unstructured":"Huang, H., Liang, R., Lv, C., Lu, M., Gong, D., Yin, S.: Two-stage robust stochastic scheduling for energy recovery in coal mine integrated energy system. Appl. Energy 290, 116759 (2021)","journal-title":"Appl. Energy"},{"key":"11_CR4","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2024.3378774","author":"R Zheng","year":"2024","unstructured":"Zheng, R., Zhang, Y., Sun, X., Gong, D., Gao, X.: An interval multiobjective evolutionary generation algorithm for product design change plans in uncertain environments. IEEE Trans. Evol. Comput. (2024). https:\/\/doi.org\/10.1109\/TEVC.2024.3378774","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"3","key":"11_CR5","doi-asserted-by":"publisher","first-page":"1058","DOI":"10.1049\/cit2.12176","volume":"8","author":"R Zheng","year":"2023","unstructured":"Zheng, R., et al.: Multi-objective particle swarm optimisation of complex product change plan considering service performance. CAAI Trans. Intell. Technol. 8(3), 1058\u20131076 (2023)","journal-title":"CAAI Trans. Intell. Technol."},{"key":"11_CR6","doi-asserted-by":"publisher","DOI":"10.1016\/j.jobe.2020.101505","volume":"32","author":"Y Zhang","year":"2020","unstructured":"Zhang, Y., Yuan, L., Zhang, Q., Sun, X.: Multi-objective optimization of building energy performance using a particle swarm optimizer with less control parameters. J. Build. Eng. 32, 101505 (2020)","journal-title":"J. Build. Eng."},{"issue":"17","key":"11_CR7","doi-asserted-by":"publisher","first-page":"6227","DOI":"10.1080\/00207543.2024.2311183","volume":"62","author":"D Thiruvady","year":"2024","unstructured":"Thiruvady, D., Nguyen, S., Sun, Y., Shiri, F., Zaidi, N., Li, X.: Adaptive population-based simulated annealing for resource constrained job scheduling with uncertainty. Int. J. Prod. Res. 62(17), 6227\u20136250 (2024)","journal-title":"Int. J. Prod. Res."},{"issue":"3","key":"11_CR8","doi-asserted-by":"publisher","first-page":"642","DOI":"10.1109\/TEVC.2022.3175065","volume":"27","author":"K Qiao","year":"2023","unstructured":"Qiao, K., et al.: Dynamic auxiliary task-based evolutionary multitasking for constrained multi-objective optimization. IEEE Trans. Evol. Comput. 27(3), 642\u2013656 (2023)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"11_CR9","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.119258","volume":"215","author":"Q Bao","year":"2023","unstructured":"Bao, Q., Wang, M., Dai, G., Chen, X., Song, Z., Li, S.: A dual population based bidirectional coevolution algorithm for constrained multi-objective optimization problems. Expert Syst. Appl. 215, 119258 (2023)","journal-title":"Expert Syst. Appl."},{"issue":"3","key":"11_CR10","doi-asserted-by":"publisher","first-page":"1450","DOI":"10.1109\/TCYB.2025.3531449","volume":"55","author":"J Ma","year":"2025","unstructured":"Ma, J., Zhang, Y., Gong, D., Gao, X., Peng, C.: Two-stage cooperation multiobjective evolutionary algorithm guided by constraint-sensitive variables. IEEE Trans. Cybern. 55(3), 1450\u20131463 (2025)","journal-title":"IEEE Trans. Cybern."},{"key":"11_CR11","unstructured":"Huang, W., Wang, R., Zhang, T., Qi, S., Wang, L.: Evolutionary algorithm with detection region method for constrained multi-objective problems with binary constraints. (2024). arXiv:2411.08437v1"},{"key":"11_CR12","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2024.3425629","author":"S Li","year":"2024","unstructured":"Li, S., Li, K., Li, W., Yang, M.: Evolutionary alternating direction method of multipliers for constrained multi-objective optimization with unknown constraints. IEEE Trans. Evol. Comput. (2024). https:\/\/doi.org\/10.1109\/TEVC.2024.3425629","journal-title":"IEEE Trans. Evol. Comput."},{"key":"11_CR13","doi-asserted-by":"publisher","first-page":"363","DOI":"10.1016\/j.asoc.2013.10.008","volume":"14","author":"L Jiao","year":"2014","unstructured":"Jiao, L., Luo, J., Shang, R., Liu, F.: A modified objective function method with feasible-guiding strategy to solve constrained multi-objective optimization problems. Appl. Soft Comput. 14, 363\u2013380 (2014)","journal-title":"Appl. Soft Comput."},{"issue":"1","key":"11_CR14","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1109\/TCYB.2021.3069814","volume":"53","author":"Z Ma","year":"2023","unstructured":"Ma, Z., Wang, Y.: Shift-based penalty for evolutionary constrained multiobjective optimization and its application. IEEE Trans. Cybern. 53(1), 18\u201330 (2023)","journal-title":"IEEE Trans. Cybern."},{"issue":"2","key":"11_CR15","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."},{"key":"11_CR16","doi-asserted-by":"crossref","unstructured":"Takahama, T., Sakai, S.: Constrained optimization by the constrained differential evolution with gradient-based mutation and feasible elites. In 2006 IEEE International Conference on Evolutionary Computation, pp. 1\u20138. IEEE(2006)","DOI":"10.1109\/CEC.2006.1688283"},{"issue":"3","key":"11_CR17","doi-asserted-by":"publisher","first-page":"284","DOI":"10.1109\/4235.873238","volume":"4","author":"TP Runarsson","year":"2000","unstructured":"Runarsson, T.P., Yao, X.: Stochastic ranking for constrained evolutionary optimization. IEEE Trans. Evol. Comput. 4(3), 284\u2013294 (2000)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"11_CR18","doi-asserted-by":"publisher","first-page":"665","DOI":"10.1016\/j.swevo.2018.08.017","volume":"44","author":"Z Fan","year":"2019","unstructured":"Fan, Z., et al.: Push and pull search for solving constrained multi-objective optimization problems. Swarm Evol. Comput. 44, 665\u2013679 (2019)","journal-title":"Swarm Evol. Comput."},{"key":"11_CR19","doi-asserted-by":"publisher","DOI":"10.1016\/j.swevo.2022.101166","volume":"75","author":"Y Wang","year":"2022","unstructured":"Wang, Y., Liu, Y., Zou, J., Zheng, J., Yang, S.: A novel two-phase evolutionary algorithm for solving constrained multi-objective optimization problems. Swarm Evol. Comput. 75, 101166 (2022)","journal-title":"Swarm Evol. Comput."},{"issue":"1","key":"11_CR20","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1109\/TEVC.2022.3230822","volume":"28","author":"F Ming","year":"2024","unstructured":"Ming, F., Gong, W., Wang, L., Gao, L.: Constrained multi-objective optimization via multitasking and knowledge transfer. IEEE Trans. Evol. Comput. 28(1), 77\u201389 (2024)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"11_CR21","doi-asserted-by":"crossref","unstructured":"Ban, X., Liang, J., Yu, K., Wang, Y., Qiao, K., Peng, J., Gong, D., Dai, C.: A local knowledge transfer-based evolutionary algorithm for constrained multitask optimization. IEEE Trans. Syst., Man, Cybern., Syst. 55(3), 2183\u20132195(2025)","DOI":"10.1109\/TSMC.2024.3520322"},{"issue":"1","key":"11_CR22","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1109\/TEVC.2022.3155593","volume":"27","author":"S Liu","year":"2023","unstructured":"Liu, S., Li, J., Lin, Q., Tian, Y., Tan, K.C.: Learning to accelerate evolutionary search for large-scale multiobjective optimization. IEEE Trans. Evol. Comput. 27(1), 67\u201381 (2023)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"11_CR23","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2024.3380366","author":"S Liu","year":"2024","unstructured":"Liu, S., Wang, Z., Lin, Q., Li, J., Tan, K.C.: Learning-aided evolutionary search and selection for scaling-up constrained multiobjective optimization. IEEE Trans. Evol. Comput. (2024). https:\/\/doi.org\/10.1109\/TEVC.2024.3380366","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"4","key":"11_CR24","doi-asserted-by":"publisher","first-page":"525","DOI":"10.1016\/S0893-6080(05)80056-5","volume":"6","author":"MF M\u00f8ller","year":"1993","unstructured":"M\u00f8ller, M.F.: A scaled conjugate gradient algorithm for fast supervised learning. Neural Netw. 6(4), 525\u2013533 (1993)","journal-title":"Neural Netw."},{"issue":"3","key":"11_CR25","doi-asserted-by":"publisher","first-page":"339","DOI":"10.1162\/evco_a_00259","volume":"28","author":"Z Fan","year":"2020","unstructured":"Fan, Z., et al.: Difficulty adjustable and scalable constrained multi-objective test problem toolkit. Evol. Comput. 28(3), 339\u2013378 (2020)","journal-title":"Evol. Comput."},{"issue":"4","key":"11_CR26","doi-asserted-by":"publisher","first-page":"602","DOI":"10.1109\/TEVC.2013.2281534","volume":"18","author":"H Jain","year":"2014","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 (2014)","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"5","key":"11_CR27","doi-asserted-by":"publisher","first-page":"870","DOI":"10.1109\/TEVC.2019.2894743","volume":"23","author":"Z Liu","year":"2019","unstructured":"Liu, Z., Wang, Y.: Handling constrained multiobjective optimization problems with constraints in both the decision and objective spaces. IEEE Trans. Evol. Comput. 23(5), 870\u2013884 (2019)","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"1","key":"11_CR28","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1109\/TEVC.2023.3260306","volume":"28","author":"J Zou","year":"2024","unstructured":"Zou, J., et al.: A multi-population evolutionary algorithm using new cooperative mechanism for solving multi-objective problems with multi-constraint. IEEE Trans. Evol. Comput. 28(1), 267\u2013280 (2024)","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"2","key":"11_CR29","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1007\/s10710-005-6164-x","volume":"6","author":"CAC Coello","year":"2005","unstructured":"Coello, C.A.C., Cortes, N.C.: Solving multiobjective optimization problems using an artificial immune system. Genet. Program. Evol. M. 6(2), 163\u2013190 (2005)","journal-title":"Genet. Program. Evol. M."},{"issue":"4","key":"11_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.: Multiobjective evolutionary algorithms: A comparative case study and the strength Pareto approach. IEEE Trans. Evol. Comput. 3(4), 257\u2013271 (1999)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"11_CR31","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. IEEE Comput. Intell. Mag. 12, 73\u201387 (2017)","journal-title":"IEEE Comput. Intell. Mag."}],"container-title":["Lecture Notes in Computer Science","Advanced Intelligent Computing Technology and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-96-9805-9_11","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T17:58:44Z","timestamp":1783101524000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-96-9805-9_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9789819698042","9789819698059"],"references-count":31,"URL":"https:\/\/doi.org\/10.1007\/978-981-96-9805-9_11","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"26 July 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Ningbo","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":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 July 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 July 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/icg\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}