{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T19:52:19Z","timestamp":1743018739637,"version":"3.40.3"},"publisher-location":"Cham","reference-count":21,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030041786"},{"type":"electronic","value":"9783030041793"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-030-04179-3_38","type":"book-chapter","created":{"date-parts":[[2018,11,17]],"date-time":"2018-11-17T07:12:42Z","timestamp":1542438762000},"page":"430-441","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["An Artificial Neural Network for Distributed Constrained Optimization"],"prefix":"10.1007","author":[{"given":"Na","family":"Liu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenwen","family":"Jia","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sitian","family":"Qin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guocheng","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,11,18]]},"reference":[{"issue":"3","key":"38_CR1","doi-asserted-by":"publisher","first-page":"781","DOI":"10.1109\/TAC.2013.2278132","volume":"59","author":"B Gharesifard","year":"2014","unstructured":"Gharesifard, B., Cort\u00e9s, J.: Distributed continuous-time convex optimization on weight-balanced digraphs. IEEE Trans. Autom. Control 59(3), 781\u2013786 (2014)","journal-title":"IEEE Trans. Autom. Control"},{"key":"38_CR2","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"246","DOI":"10.1007\/3-540-47745-4_11","volume-title":"Multi-Agent Systems and Applications","author":"D Kazakov","year":"2001","unstructured":"Kazakov, D., Kudenko, D.: Machine learning and inductive logic programming for multi-agent systems. In: Luck, M., Ma\u0159\u00edk, V., \u0160t\u011bp\u00e1nkov\u00e1, O., Trappl, R. (eds.) ACAI 2001. LNCS (LNAI), vol. 2086, pp. 246\u2013270. Springer, Heidelberg (2001). https:\/\/doi.org\/10.1007\/3-540-47745-4_11"},{"key":"38_CR3","doi-asserted-by":"publisher","first-page":"254","DOI":"10.1016\/j.automatica.2015.03.001","volume":"55","author":"SS Kia","year":"2015","unstructured":"Kia, S.S., Cort, J., Martnez, S.: Distributed convex optimization via continuous-time coordination algorithms with discrete-time communication. Automatica 55, 254\u2013264 (2015)","journal-title":"Automatica"},{"issue":"5","key":"38_CR4","doi-asserted-by":"publisher","first-page":"1434","DOI":"10.1109\/TAC.2017.2750103","volume":"63","author":"Z Li","year":"2018","unstructured":"Li, Z., Ding, Z., Sun, J., Li, Z.: Distributed adaptive convex optimization on directed graphs via continuous-time algorithms. IEEE Trans. Autom. Control 63(5), 1434\u20131441 (2018)","journal-title":"IEEE Trans. Autom. Control"},{"issue":"8","key":"38_CR5","doi-asserted-by":"publisher","first-page":"1747","DOI":"10.1109\/TNNLS.2016.2549566","volume":"28","author":"Q Liu","year":"2017","unstructured":"Liu, Q., Yang, S., Wang, J.: A collective neurodynamic approach to distributed constrained optimization. IEEE Trans. Neural Netw. Learn. Syst. 28(8), 1747\u20131758 (2017)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"issue":"12","key":"38_CR6","doi-asserted-by":"publisher","first-page":"3310","DOI":"10.1109\/TAC.2015.2416927","volume":"60","author":"Q Liu","year":"2015","unstructured":"Liu, Q., Wang, J.: A second-order multi-agent network for bound-constrained distributed optimization. IEEE Trans. Autom. Control 60(12), 3310\u20133315 (2015)","journal-title":"IEEE Trans. Autom. Control"},{"issue":"9","key":"38_CR7","doi-asserted-by":"publisher","first-page":"2348","DOI":"10.1109\/TAC.2012.2184199","volume":"57","author":"J Lu","year":"2011","unstructured":"Lu, J., Tang, C.: Zero-gradient-sum algorithms for distributed convex optimization: the continuous-time case. IEEE Trans. Autom. Control 57(9), 2348\u20132354 (2011)","journal-title":"IEEE Trans. Autom. Control"},{"issue":"1","key":"38_CR8","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1109\/TAC.2008.2009515","volume":"54","author":"A Nedic","year":"2009","unstructured":"Nedic, A., Ozdaglar, A.: Distributed subgradient methods for multi-agent optimization. IEEE Trans. Autom. Control 54(1), 48\u201361 (2009)","journal-title":"IEEE Trans. Autom. Control"},{"issue":"4","key":"38_CR9","doi-asserted-by":"publisher","first-page":"922","DOI":"10.1109\/TAC.2010.2041686","volume":"55","author":"A Nedic","year":"2010","unstructured":"Nedic, A., Ozdaglar, A., Parrilo, P.A.: Constrained consensus and optimization in multi-agent networks. IEEE Trans. Autom. Control 55(4), 922\u2013938 (2010)","journal-title":"IEEE Trans. Autom. Control"},{"key":"38_CR10","volume-title":"Distributed Event-Triggered Coordination for Average Consensus on Weight-Balanced Digraphs","author":"C Nowzari","year":"2016","unstructured":"Nowzari, C.: Distributed Event-Triggered Coordination for Average Consensus on Weight-Balanced Digraphs. Pergamon Press Inc., Oxford (2016)"},{"key":"38_CR11","doi-asserted-by":"publisher","first-page":"655","DOI":"10.1016\/j.neucom.2013.01.025","volume":"120","author":"S Qin","year":"2013","unstructured":"Qin, S., Bian, W., Xue, X.: A new one-layer recurrent neural network for nonsmooth pseudoconvex optimization. Neurocomputing 120, 655\u2013662 (2013)","journal-title":"Neurocomputing"},{"key":"38_CR12","doi-asserted-by":"publisher","first-page":"272","DOI":"10.1016\/j.neunet.2014.12.007","volume":"63","author":"S Qin","year":"2015","unstructured":"Qin, S., Fan, D., Wu, G., Zhao, L.: Neural network for constrained nonsmooth optimization using Tikhonov regularization. Neural Netw. 63, 272\u2013281 (2015)","journal-title":"Neural Netw."},{"key":"38_CR13","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TNNLS.2016.2574830","volume":"99","author":"S Qin","year":"2016","unstructured":"Qin, S., Feng, J., Song, J., Wen, X., Xu, C.: A one-layer recurrent neural network for constrained complex-variable convex optimization. IEEE Trans. Neural Netw. Learn. Syst. 99, 1\u201311 (2016)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"issue":"10","key":"38_CR14","doi-asserted-by":"publisher","first-page":"3063","DOI":"10.1109\/TCYB.2016.2567449","volume":"47","author":"S Qin","year":"2017","unstructured":"Qin, S., Yang, X., Xue, X., Song, J.: A one-layer recurrent neural network for pseudoconvex optimization problems with equality and inequality constraints. IEEE Trans. Cybern. 47(10), 3063\u20133074 (2017)","journal-title":"IEEE Trans. Cybern."},{"key":"38_CR15","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1016\/j.automatica.2016.01.055","volume":"68","author":"Z Qiu","year":"2016","unstructured":"Qiu, Z., Liu, S., Xie, L.: Distributed constrained optimal consensus of multi-agent systems. Automatica 68, 209\u2013215 (2016)","journal-title":"Automatica"},{"key":"38_CR16","unstructured":"Rich, E.: Artificial Intelligence. E. Horwood (1985)"},{"issue":"3","key":"38_CR17","doi-asserted-by":"publisher","first-page":"610","DOI":"10.1109\/TAC.2012.2215261","volume":"58","author":"G Shi","year":"2013","unstructured":"Shi, G., Johansson, K.H., Hong, Y.: Reaching an optimal consensus: dynamical systems that compute intersections of convex sets. IEEE Trans. Autom. Control 58(3), 610\u2013622 (2013)","journal-title":"IEEE Trans. Autom. Control"},{"key":"38_CR18","doi-asserted-by":"crossref","unstructured":"Wang, J., Elia, N.: A control perspective for centralized and distributed convex optimization. In: Decision and Control and European Control Conference, pp. 3800\u20133805 (2011)","DOI":"10.1109\/CDC.2011.6161503"},{"key":"38_CR19","doi-asserted-by":"crossref","unstructured":"Wei, E., Ozdaglar, A., Jadbabaie, A.: A distributed newton method for network utility maximization. In: 2010 49th IEEE Conference on Decision and Control (CDC), pp. 1816\u20131821 (2010)","DOI":"10.1109\/CDC.2010.5718026"},{"key":"38_CR20","unstructured":"White, S.M.: Social engineering. In: IEEE International Conference and Workshop on the Engineering of Computer-Based Systems, 2003 Proceedings, pp. 261\u2013267 (2003)"},{"issue":"5","key":"38_CR21","doi-asserted-by":"publisher","first-page":"717","DOI":"10.1109\/TSMC.2016.2531649","volume":"47","author":"S Yang","year":"2017","unstructured":"Yang, S., Liu, Q., Wang, J.: Distributed optimization based on a multiagent system in the presence of communication delays. IEEE Trans. Syst. Man Cybern. Syst. 47(5), 717\u2013728 (2017)","journal-title":"IEEE Trans. Syst. Man Cybern. Syst."}],"container-title":["Lecture Notes in Computer Science","Neural Information Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-04179-3_38","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,7]],"date-time":"2024-03-07T15:30:17Z","timestamp":1709825417000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-04179-3_38"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783030041786","9783030041793"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-04179-3_38","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"18 November 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICONIP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Neural Information Processing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Siem Reap","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Cambodia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 December 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 December 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iconip2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/conference.cs.cityu.edu.hk\/iconip\/","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":"575","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":"401","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":"70% - 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":"4","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":"6","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)"}}]}}