{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,20]],"date-time":"2026-02-20T04:48:15Z","timestamp":1771562895479,"version":"3.50.1"},"publisher-location":"Cham","reference-count":48,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030263683","type":"print"},{"value":"9783030263690","type":"electronic"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"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":[[2019]]},"DOI":"10.1007\/978-3-030-26369-0_1","type":"book-chapter","created":{"date-parts":[[2019,7,18]],"date-time":"2019-07-18T16:02:47Z","timestamp":1563465767000},"page":"3-17","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Generative Adversarial Optimization"],"prefix":"10.1007","author":[{"given":"Ying","family":"Tan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bo","family":"Shi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,7,19]]},"reference":[{"key":"1_CR1","unstructured":"Arjovsky, M., Chintala, S., Bottou, L.: Wasserstein GAN. arXiv preprint arXiv:1701.07875 (2017)"},{"key":"1_CR2","unstructured":"Auger, A., Hansen, N.: A restart cma evolution strategy with increasing population size. In: 2005 IEEE Congress on Evolutionary Computation, vol. 2, pp. 1769\u20131776. IEEE (2005)"},{"key":"1_CR3","unstructured":"Che, T., et al.: Maximum-likelihood augmented discrete generative adversarial networks. arXiv preprint arXiv:1702.07983 (2017)"},{"issue":"3","key":"1_CR4","doi-asserted-by":"publisher","first-page":"680","DOI":"10.1109\/TSMCA.2009.2012436","volume":"39","author":"J Chen","year":"2009","unstructured":"Chen, J., Xin, B., Peng, Z., Dou, L., Zhang, J.: Optimal contraction theorem for exploration-exploitation tradeoff in search and optimization. IEEE Trans. Syst. Man Cybern. Part A Syst. Hum. 39(3), 680\u2013691 (2009)","journal-title":"IEEE Trans. Syst. Man Cybern. Part A Syst. Hum."},{"key":"1_CR5","unstructured":"Chongxuan, L., Xu, T., Zhu, J., Zhang, B.: Triple generative adversarial nets. In: Advances in Neural Information Processing Systems, pp. 4088\u20134098 (2017)"},{"key":"1_CR6","doi-asserted-by":"crossref","unstructured":"Clerc, M.: Standard particle swarm optimisation from 2006 to 2011. Part. Swarm Cent. 253 (2011)","DOI":"10.1002\/9780470612163"},{"key":"1_CR7","unstructured":"Dai, W., et al.: Scan: structure correcting adversarial network for chest X-rays organ segmentation. arXiv preprint arXiv:1703.08770 (2017)"},{"key":"1_CR8","volume-title":"Handbook of Genetic Algorithms","author":"L Davis","year":"1991","unstructured":"Davis, L.: Handbook of Genetic Algorithms. Van Nostrand Reinhold, New York (1991)"},{"key":"1_CR9","unstructured":"Denton, E., Gross, S., Fergus, R.: Semi-supervised learning with context-conditional generative adversarial networks. arXiv preprint arXiv:1611.06430 (2016)"},{"key":"1_CR10","unstructured":"Denton, E.L., Chintala, S., Fergus, R., et al.: Deep generative image models using a Laplacian pyramid of adversarial networks. In: Advances in Neural Information Processing Systems, pp. 1486\u20131494 (2015)"},{"key":"1_CR11","unstructured":"Dorigo, M., Di Caro, G.: Ant colony optimization: a new meta-heuristic. In: Proceedings of the 1999 Congress on Evolutionary Computation-CEC 1999 (Cat. No. 99TH8406), vol. 2, pp. 1470\u20131477. IEEE (1999)"},{"issue":"1","key":"1_CR12","first-page":"2096","volume":"17","author":"Y Ganin","year":"2016","unstructured":"Ganin, Y., et al.: Domain-adversarial training of neural networks. J. Mach. Learn. Res. 17(1), 2096\u20133030 (2016)","journal-title":"J. Mach. Learn. Res."},{"key":"1_CR13","unstructured":"Goodfellow, I., et al.: Generative adversarial nets. In: Advances in Neural Information Processing Systems, pp. 2672\u20132680 (2014)"},{"key":"1_CR14","unstructured":"Guimaraes, G.L., Sanchez-Lengeling, B., Outeiral, C., Farias, P.L.C., Aspuru-Guzik, A.: Objective-reinforced generative adversarial networks (organ) for sequence generation models. arXiv preprint arXiv:1705.10843 (2017)"},{"key":"1_CR15","unstructured":"Gulrajani, I., Ahmed, F., Arjovsky, M., Dumoulin, V., Courville, A.C.: Improved training of Wasserstein GANs. In: Advances in Neural Information Processing Systems, pp. 5767\u20135777 (2017)"},{"key":"1_CR16","unstructured":"Hu, W.W., Tan, Y.: Generating adversarial malware examples for black-box attacks based on GAN (2017)"},{"key":"1_CR17","doi-asserted-by":"crossref","unstructured":"Isola, P., Zhu, J.Y., Zhou, T., Efros, A.A.: Image-to-image translation with conditional adversarial networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1125\u20131134 (2017)","DOI":"10.1109\/CVPR.2017.632"},{"key":"1_CR18","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1007\/0-387-27705-6_6","volume-title":"Handbook of Nature-Inspired and Innovative Computing","author":"J Kennedy","year":"2006","unstructured":"Kennedy, J.: Swarm intelligence. In: Zomaya, A.Y. (ed.) Handbook of Nature-Inspired and Innovative Computing, pp. 187\u2013219. Springer, Boston (2006). https:\/\/doi.org\/10.1007\/0-387-27705-6_6"},{"key":"1_CR19","doi-asserted-by":"publisher","first-page":"760","DOI":"10.1007\/978-0-387-30164-8","volume-title":"Encyclopedia of Machine Learning","author":"J Kennedy","year":"2010","unstructured":"Kennedy, J.: Particle swarm optimization. In: Sammut, C., Webb, G.I. (eds.) Encyclopedia of Machine Learning, pp. 760\u2013766. Springer, Boston (2010). https:\/\/doi.org\/10.1007\/978-0-387-30164-8"},{"key":"1_CR20","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-20859-1","volume-title":"Computational Optimization, Methods and Algorithms","author":"S Koziel","year":"2011","unstructured":"Koziel, S., Yang, X.S.: Computational Optimization, Methods and Algorithms, vol. 356. Springer, Heidelberg (2011). https:\/\/doi.org\/10.1007\/978-3-642-20859-1"},{"key":"1_CR21","unstructured":"Kusner, M.J., Hern\u00e1ndez-Lobato, J.M.: GANs for sequences of discrete elements with the Gumbel-softmax distribution. arXiv preprint arXiv:1611.04051 (2016)"},{"key":"1_CR22","doi-asserted-by":"crossref","unstructured":"Ledig, C., et al.: Photo-realistic single image super-resolution using a generative adversarial network. In: Proceedings of the IEEE conference on Computer Vision and Pattern Recognition, pp. 4681\u20134690 (2017)","DOI":"10.1109\/CVPR.2017.19"},{"key":"1_CR23","doi-asserted-by":"crossref","unstructured":"Lehman, J., Chen, J., Clune, J., Stanley, K.O.: Safe mutations for deep and recurrent neural networks through output gradients. In: Proceedings of the Genetic and Evolutionary Computation Conference, pp. 117\u2013124. ACM (2018)","DOI":"10.1145\/3205455.3205473"},{"issue":"5","key":"1_CR24","doi-asserted-by":"publisher","first-page":"679","DOI":"10.1109\/TEVC.2017.2787042","volume":"22","author":"J Li","year":"2018","unstructured":"Li, J., Tan, Y.: Loser-out tournament-based fireworks algorithm for multimodal function optimization. IEEE Trans. Evol. Comput. 22(5), 679\u2013691 (2018)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"1_CR25","doi-asserted-by":"crossref","unstructured":"Li, J., Zheng, S., Tan, Y.: Adaptive fireworks algorithm. In: 2014 IEEE Congress on Evolutionary Computation (CEC), pp. 3214\u20133221. IEEE (2014)","DOI":"10.1109\/CEC.2014.6900418"},{"issue":"1","key":"1_CR26","doi-asserted-by":"publisher","first-page":"153","DOI":"10.1109\/TEVC.2016.2589821","volume":"21","author":"J Li","year":"2017","unstructured":"Li, J., Zheng, S., Tan, Y.: The effect of information utilization: Introducing a novel guiding spark in the fireworks algorithm. IEEE Trans. Evol. Comput. 21(1), 153\u2013166 (2017)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"1_CR27","unstructured":"Liang, J., Qu, B., Suganthan, P., Hern\u00e1ndez-D\u00edaz, A.G.: Problem definitions and evaluation criteria for the CEC 2013 special session on real-parameter optimization. Technical report 201212(34), Computational Intelligence Laboratory, Zhengzhou University, Zhengzhou, China and Nanyang Technological University, Singapore, pp. 281\u2013295 (2013)"},{"key":"1_CR28","doi-asserted-by":"crossref","unstructured":"Mao, X., Li, Q., Xie, H., Lau, R.Y., Wang, Z., Paul Smolley, S.: Least squares generative adversarial networks. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2794\u20132802 (2017)","DOI":"10.1109\/ICCV.2017.304"},{"issue":"4","key":"1_CR29","doi-asserted-by":"publisher","first-page":"965","DOI":"10.1007\/s10462-012-9342-2","volume":"42","author":"M Neshat","year":"2014","unstructured":"Neshat, M., Sepidnam, G., Sargolzaei, M., Toosi, A.N.: Artificial fish swarm algorithm: a survey of the state-of-the-art, hybridization, combinatorial and indicative applications. Artif. Intell. Rev. 42(4), 965\u2013997 (2014)","journal-title":"Artif. Intell. Rev."},{"key":"1_CR30","unstructured":"Nowozin, S., Cseke, B., Tomioka, R.: f-GAN: training generative neural samplers using variational divergence minimization. In: Advances in Neural Information Processing Systems, pp. 271\u2013279 (2016)"},{"issue":"2","key":"1_CR31","doi-asserted-by":"publisher","first-page":"398","DOI":"10.1109\/TEVC.2008.927706","volume":"13","author":"AK Qin","year":"2009","unstructured":"Qin, A.K., Huang, V.L., Suganthan, P.N.: Differential evolution algorithm with strategy adaptation for global numerical optimization. IEEE Trans. Evol. Comput. 13(2), 398\u2013417 (2009)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"1_CR32","unstructured":"Radford, A., Metz, L., Chintala, S.: Unsupervised representation learning with deep convolutional generative adversarial networks. arXiv preprint arXiv:1511.06434 (2015)"},{"key":"1_CR33","unstructured":"Ruder, S.: An overview of gradient descent optimization algorithms. arXiv preprint arXiv:1609.04747 (2016)"},{"key":"1_CR34","unstructured":"Salimans, T., Goodfellow, I., Zaremba, W., Cheung, V., Radford, A., Chen, X.: Improved techniques for training GANs. In: Advances in Neural Information Processing Systems, pp. 2234\u20132242 (2016)"},{"key":"1_CR35","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"534","DOI":"10.1007\/978-3-319-77380-3_51","volume-title":"Advances in Multimedia Information Processing \u2013 PCM 2017","author":"H Shi","year":"2018","unstructured":"Shi, H., Dong, J., Wang, W., Qian, Y., Zhang, X.: SSGAN: secure steganography based on generative adversarial networks. In: Zeng, B., Huang, Q., El Saddik, A., Li, H., Jiang, S., Fan, X. (eds.) PCM 2017. LNCS, vol. 10735, pp. 534\u2013544. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-77380-3_51"},{"issue":"4","key":"1_CR36","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-a simple and efficient heuristic for global optimization over continuous spaces. J. Glob. Optim. 11(4), 341\u2013359 (1997)","journal-title":"J. Glob. Optim."},{"key":"1_CR37","unstructured":"Such, F.P., Madhavan, V., Conti, E., Lehman, J., Stanley, K.O., Clune, J.: Deep neuroevolution: genetic algorithms are a competitive alternative for training deep neural networks for reinforcement learning. arXiv preprint arXiv:1712.06567 (2017)"},{"issue":"2","key":"1_CR38","doi-asserted-by":"publisher","first-page":"701","DOI":"10.1016\/j.ejor.2008.07.025","volume":"197","author":"KC Tan","year":"2009","unstructured":"Tan, K.C., Chiam, S.C., Mamun, A., Goh, C.K.: Balancing exploration and exploitation with adaptive variation for evolutionary multi-objective optimization. Eur. J. Oper. Res. 197(2), 701\u2013713 (2009)","journal-title":"Eur. J. Oper. Res."},{"key":"1_CR39","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-662-46353-6","volume-title":"Fireworks Algorithm","author":"Y Tan","year":"2015","unstructured":"Tan, Y.: Fireworks Algorithm. Springer, Heidelberg (2015). https:\/\/doi.org\/10.1007\/978-3-662-46353-6"},{"key":"1_CR40","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"355","DOI":"10.1007\/978-3-642-13495-1_44","volume-title":"Advances in Swarm Intelligence","author":"Y Tan","year":"2010","unstructured":"Tan, Y., Zhu, Y.: Fireworks algorithm for optimization. In: Tan, Y., Shi, Y., Tan, K.C. (eds.) ICSI 2010. LNCS, vol. 6145, pp. 355\u2013364. Springer, Heidelberg (2010). https:\/\/doi.org\/10.1007\/978-3-642-13495-1_44"},{"key":"1_CR41","doi-asserted-by":"crossref","unstructured":"Tulyakov, S., Liu, M.Y., Yang, X., Kautz, J.: MoCoGAN: decomposing motion and content for video generation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1526\u20131535 (2018)","DOI":"10.1109\/CVPR.2018.00165"},{"key":"1_CR42","unstructured":"Vondrick, C., Pirsiavash, H., Torralba, A.: Generating videos with scene dynamics. In: Advances In Neural Information Processing Systems, pp. 613\u2013621 (2016)"},{"key":"1_CR43","unstructured":"Wu, J., Zhang, C., Xue, T., Freeman, B., Tenenbaum, J.: Learning a probabilistic latent space of object shapes via 3D generative-adversarial modeling. In: Advances in Neural Information Processing Systems, pp. 82\u201390 (2016)"},{"key":"1_CR44","doi-asserted-by":"crossref","unstructured":"Yu, L., Zhang, W., Wang, J., Yu, Y.: SeqGAN: sequence generative adversarial nets with policy gradient. In: Thirty-First AAAI Conference on Artificial Intelligence (2017)","DOI":"10.1609\/aaai.v31i1.10804"},{"key":"1_CR45","doi-asserted-by":"crossref","unstructured":"Zheng, S., Janecek, A., Li, J., Tan, Y.: Dynamic search in fireworks algorithm. In: 2014 IEEE Congress on Evolutionary Computation (CEC), pp. 3222\u20133229. IEEE (2014)","DOI":"10.1109\/CEC.2014.6900485"},{"key":"1_CR46","doi-asserted-by":"crossref","unstructured":"Zheng, S., Janecek, A., Tan, Y.: Enhanced fireworks algorithm. In: 2013 IEEE Congress on Evolutionary Computation, pp. 2069\u20132077. IEEE (2013)","DOI":"10.1109\/CEC.2013.6557813"},{"issue":"1","key":"1_CR47","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1109\/TCBB.2015.2497227","volume":"14","author":"S Zheng","year":"2017","unstructured":"Zheng, S., Li, J., Janecek, A., Tan, Y.: A cooperative framework for fireworks algorithm. IEEE\/ACM Trans. Comput. Biol. Bioinform. (TCBB) 14(1), 27\u201341 (2017)","journal-title":"IEEE\/ACM Trans. Comput. Biol. Bioinform. (TCBB)"},{"key":"1_CR48","doi-asserted-by":"crossref","unstructured":"Zhu, J.Y., Park, T., Isola, P., Efros, A.A.: Unpaired image-to-image translation using cycle-consistent adversarial networks. In: 2017 IEEE International Conference on Computer Vision (ICCV) (2017)","DOI":"10.1109\/ICCV.2017.244"}],"container-title":["Lecture Notes in Computer Science","Advances in Swarm Intelligence"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-26369-0_1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,24]],"date-time":"2022-09-24T05:07:58Z","timestamp":1663996078000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-26369-0_1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030263683","9783030263690"],"references-count":48,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-26369-0_1","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"19 July 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICSI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Swarm Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Chiang Mai","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Thailand","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 July 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30 July 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"swarm2019a","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-si.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}