{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T02:00:40Z","timestamp":1767319240058,"version":"3.48.0"},"publisher-location":"Cham","reference-count":28,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032091550","type":"print"},{"value":"9783032091567","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"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":[[2026]]},"DOI":"10.1007\/978-3-032-09156-7_17","type":"book-chapter","created":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T01:58:35Z","timestamp":1767319115000},"page":"253-264","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Time-Varying Multi-objective Optimization: Tradeoff Regret Bounds"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1415-2166","authenticated-orcid":false,"given":"Allahkaram","family":"Shafiei","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0839-0691","authenticated-orcid":false,"given":"Jakub","family":"Marecek","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,1,2]]},"reference":[{"issue":"2","key":"17_CR1","doi-asserted-by":"publisher","first-page":"416","DOI":"10.1007\/s10957-012-0167-6","volume":"157","author":"AM Bagirov","year":"2013","unstructured":"Bagirov, A.M., Jin, L., Karmitsa, N., Al Nuaimat, A., Sultanova, N.: Subgradient method for nonconvex nonsmooth optimization. J. Optim. Theory Appl. 157(2), 416\u2013435 (2013). https:\/\/doi.org\/10.1007\/s10957-012-0167-6","journal-title":"J. Optim. Theory Appl."},{"issue":"1","key":"17_CR2","doi-asserted-by":"publisher","first-page":"725","DOI":"10.1109\/61.19265","volume":"4","author":"M Baran","year":"1989","unstructured":"Baran, M., Wu, F.: Optimal capacitor placement on radial distribution systems. IEEE Trans. Power Del. 4(1), 725\u2013734 (1989). https:\/\/doi.org\/10.1109\/61.19265","journal-title":"IEEE Trans. Power Del."},{"issue":"4","key":"17_CR3","doi-asserted-by":"publisher","first-page":"953","DOI":"10.1137\/S1052623403429093","volume":"15","author":"H Bonnel","year":"2005","unstructured":"Bonnel, H., Iusem, A.N., Svaiter, B.F.: Proximal methods in vector optimization. SIAM J. Optim. 15(4), 953\u2013970 (2005). https:\/\/doi.org\/10.1137\/S1052623403429093","journal-title":"SIAM J. Optim."},{"issue":"4","key":"17_CR4","doi-asserted-by":"publisher","first-page":"792","DOI":"10.1109\/TEVC.2019.2958075","volume":"24","author":"Q Chen","year":"2019","unstructured":"Chen, Q., Ding, J., Yang, S., Chai, T.: A novel evolutionary algorithm for dynamic constrained multiobjective optimization problems. IEEE Trans. Evol. Comput. 24(4), 792\u2013806 (2019)","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"6","key":"17_CR5","doi-asserted-by":"publisher","first-page":"1252","DOI":"10.1109\/TRO.2007.909833","volume":"23","author":"JC Derenick","year":"2007","unstructured":"Derenick, J.C., Spletzer, J.R.: Convex optimization strategies for coordinating large-scale robot formations. IEEE Trans. Rob. 23(6), 1252\u20131259 (2007). https:\/\/doi.org\/10.1109\/TRO.2007.909833","journal-title":"IEEE Trans. Rob."},{"issue":"3","key":"17_CR6","doi-asserted-by":"publisher","first-page":"919","DOI":"10.1287\/moor.2017.0889","volume":"43","author":"D Drusvyatskiy","year":"2018","unstructured":"Drusvyatskiy, D., Lewis, A.S.: Error bounds, quadratic growth, and linear convergence of proximal methods. Math. Oper. Res. 43(3), 919\u2013948 (2018). https:\/\/doi.org\/10.1287\/moor.2017.0889","journal-title":"Math. Oper. Res."},{"key":"17_CR7","doi-asserted-by":"publisher","unstructured":"Geoffrion, A.M.: Proper efficiency and the theory of vector maximization. J. Math. Anal. Appl. 22(3), 618\u2013630 (1968). https:\/\/doi.org\/10.1016\/0022-247X(68)90201-1. https:\/\/www.sciencedirect.com\/science\/article\/pii\/0022247X68902011","DOI":"10.1016\/0022-247X(68)90201-1"},{"key":"17_CR8","unstructured":"Goh, C.K., Tan, K.C.: Evolutionary Multi-objective Optimization in Uncertain Environments. Springer, Heidelberg (2009)"},{"issue":"2","key":"17_CR9","doi-asserted-by":"publisher","first-page":"403","DOI":"10.1007\/s10589-022-00414-7","volume":"83","author":"MLN Gon\u00e7alves","year":"2022","unstructured":"Gon\u00e7alves, M.L.N., Lima, F.S., Prudente, L.F.: Globally convergent Newton-type methods for multiobjective optimization. Comput. Optim. Appl. 83(2), 403\u2013434 (2022). https:\/\/doi.org\/10.1007\/s10589-022-00414-7","journal-title":"Comput. Optim. Appl."},{"issue":"3\u20134","key":"17_CR10","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1561\/2400000013","volume":"2","author":"E Hazan","year":"2016","unstructured":"Hazan, E.: Introduction to online convex optimization. Found. Trends Optim. 2(3\u20134), 157\u2013325 (2016). https:\/\/doi.org\/10.1561\/2400000013","journal-title":"Found. Trends Optim."},{"issue":"2","key":"17_CR11","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1007\/s10994-007-5016-8","volume":"69","author":"E Hazan","year":"2007","unstructured":"Hazan, E., Agarwal, A., Kale, S.: Logarithmic regret algorithms for online convex optimization. Mach. Learn. 69(2), 169\u2013192 (2007). https:\/\/doi.org\/10.1007\/s10994-007-5016-8","journal-title":"Mach. Learn."},{"key":"17_CR12","unstructured":"Hazan, E., Singh, K., Zhang, C.: Learning linear dynamical systems via spectral filtering. In: Guyon, I., et al. (eds.) Advances in Neural Information Processing Systems, vol.\u00a030. Curran Associates, Inc. (2017)"},{"key":"17_CR13","doi-asserted-by":"crossref","unstructured":"Jahn, J.: Vector Optimization: Theory, Applications, and Extensions. Springer, Heidelberg (2010). https:\/\/books.google.cz\/books?id=7OmPtVnHeyIC","DOI":"10.1007\/978-3-642-17005-8_9"},{"issue":"4","key":"17_CR14","doi-asserted-by":"publisher","first-page":"4886","DOI":"10.1109\/TVT.2023.3330581","volume":"73","author":"H Li","year":"2023","unstructured":"Li, H., Chen, P., Yu, G., Zhou, B., Li, Y., Liao, Y.: Trajectory planning for autonomous driving in unstructured scenarios based on deep learning and quadratic optimization. IEEE Trans. Veh. Technol. 73(4), 4886\u20134903 (2023)","journal-title":"IEEE Trans. Veh. Technol."},{"key":"17_CR15","doi-asserted-by":"publisher","unstructured":"Liu, J., Marecek, J., Simonetta, A., Taka\u010d M.: A coordinate-descent algorithm for tracking solutions in time-varying optimal power flows. In: 2018 Power Systems Computation Conference (PSCC), pp.\u00a01\u20137 (2018).https:\/\/doi.org\/10.23919\/PSCC.2018.8442544","DOI":"10.23919\/PSCC.2018.8442544"},{"issue":"6","key":"17_CR16","doi-asserted-by":"publisher","first-page":"1941","DOI":"10.1109\/TEVC.2023.3250350","volume":"27","author":"S Liu","year":"2023","unstructured":"Liu, S., Lin, Q., Li, J., Tan, K.C.: A survey on learnable evolutionary algorithms for scalable multiobjective optimization. IEEE Trans. Evol. Comput. 27(6), 1941\u20131961 (2023)","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"2","key":"17_CR17","doi-asserted-by":"publisher","first-page":"40","DOI":"10.1007\/s00158-025-03973-5","volume":"68","author":"S Ma","year":"2025","unstructured":"Ma, S., Mare\u010dek, J., Kungurtsev, V., Tyburec, M.: Truss topology design under harmonic loads: peak power minimization with semidefinite programming. Struct. Multidiscip. Optim. 68(2), 40 (2025). https:\/\/doi.org\/10.1007\/s00158-025-03973-5","journal-title":"Struct. Multidiscip. Optim."},{"key":"17_CR18","doi-asserted-by":"publisher","unstructured":"Mare\u010dek, J., Mevissen, M., Villumsen, J.C.: Minlp in transmission expansion planning. In: 2016 Power Systems Computation Conference (PSCC), pp.\u00a01\u20138 (2016). https:\/\/doi.org\/10.1109\/PSCC.2016.7540906","DOI":"10.1109\/PSCC.2016.7540906"},{"key":"17_CR19","doi-asserted-by":"publisher","first-page":"369","DOI":"10.1007\/s00158-003-0368-6","volume":"26","author":"RT Marler","year":"2004","unstructured":"Marler, R.T., Arora, J.S.: Survey of multi-objective optimization methods for engineering. Struct. Multidiscip. Optim. 26, 369\u2013395 (2004)","journal-title":"Struct. Multidiscip. Optim."},{"key":"17_CR20","doi-asserted-by":"publisher","unstructured":"Ramamoorthy, V.T., Ozcan, E., Parkes, A.J., Jaouen, L., Becot, F.X.: Multi-objective topology optimisation for acoustic porous materials using gradient-based, gradient-free, and hybrid strategies. J. Acoust. Soc. Am. 153(5), 2945\u20132955 (2023). https:\/\/doi.org\/10.1121\/10.0019455","DOI":"10.1121\/10.0019455"},{"key":"17_CR21","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1007\/978-3-642-38416-5_4","volume-title":"Evolutionary Computation for Dynamic Optimization Problems","author":"C Raquel","year":"2013","unstructured":"Raquel, C., Yao, X.: Dynamic multi-objective optimization: a survey of the state-of-the-art. In: Yang, S., Yao, X. (eds.) Evolutionary Computation for Dynamic Optimization Problems, pp. 85\u2013106. Springer, Heidelberg (2013). https:\/\/doi.org\/10.1007\/978-3-642-38416-5_4"},{"issue":"11","key":"17_CR22","doi-asserted-by":"publisher","first-page":"2032","DOI":"10.1109\/JPROC.2020.3003156","volume":"108","author":"A Simonetto","year":"2020","unstructured":"Simonetto, A., Dall\u2019Anese, E., Paternain, S., Leus, G., Giannakis, G.B.: Time-varying convex optimization: time-structured algorithms and applications. Proc. IEEE 108(11), 2032\u20132048 (2020). https:\/\/doi.org\/10.1109\/JPROC.2020.3003156","journal-title":"Proc. IEEE"},{"issue":"2","key":"17_CR23","doi-asserted-by":"publisher","first-page":"339","DOI":"10.1007\/s10589-018-0043-x","volume":"72","author":"H Tanabe","year":"2019","unstructured":"Tanabe, H., Fukuda, E.H., Yamashita, N.: Proximal gradient methods for multiobjective optimization and their applications. Comput. Optim. Appl. 72(2), 339\u2013361 (2019). https:\/\/doi.org\/10.1007\/s10589-018-0043-x","journal-title":"Comput. Optim. Appl."},{"key":"17_CR24","unstructured":"Tarzanagh, D.A., Balzano, L.: Online bilevel optimization: regret analysis of online alternating gradient methods (2022). https:\/\/arxiv.org\/abs\/2207.02829v1"},{"key":"17_CR25","doi-asserted-by":"publisher","unstructured":"Wang, Z., Xu, D., Jiang, M., Tan, K.C.: Spatial-temporal knowledge transfer for dynamic constrained multiobjective optimization. IEEE Trans. Evol. Comput.\u00a0(2024). https:\/\/doi.org\/10.1109\/TEVC.2024.3449142","DOI":"10.1109\/TEVC.2024.3449142"},{"issue":"10","key":"17_CR26","doi-asserted-by":"publisher","first-page":"11240","DOI":"10.1109\/TCYB.2021.3070434","volume":"52","author":"H Zhang","year":"2022","unstructured":"Zhang, H., Ding, J., Jiang, M., Tan, K.C., Chai, T.: Inverse gaussian process modeling for evolutionary dynamic multiobjective optimization. IEEE Trans. Cybern. 52(10), 11240\u201311253 (2022). https:\/\/doi.org\/10.1109\/TCYB.2021.3070434","journal-title":"IEEE Trans. Cybern."},{"key":"17_CR27","unstructured":"Zhou, Y., Sanches\u00a0Portella, V., Schmidt, M., Harvey, N.: Regret bounds without Lipschitz continuity: online learning with relative-Lipschitz losses. In: Larochelle, H., Ranzato, M., Hadsell, R., Balcan, M., Lin, H. (eds.) Advances in Neural Information Processing Systems, vol.\u00a033, pp. 15823\u201315833. Curran Associates, Inc. (2020)"},{"key":"17_CR28","unstructured":"Zinkevich, M.: Online convex programming and generalized infinitesimal gradient ascent. In: Proceedings of the 20th International Conference on Machine Learning (ICML-03), pp. 928\u2013936 (2003)"}],"container-title":["Lecture Notes in Computer Science","Learning and Intelligent Optimization"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-09156-7_17","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T01:58:37Z","timestamp":1767319117000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-09156-7_17"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9783032091550","9783032091567"],"references-count":28,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-09156-7_17","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"2 January 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"LION","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Learning and Intelligent Optimization","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Prague","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Czech Republic","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":"15 June 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 June 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"lion2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/lion19.org","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}