{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,6]],"date-time":"2024-08-06T10:00:40Z","timestamp":1722938440948},"publisher-location":"New York, New York, USA","reference-count":28,"publisher":"ACM Press","license":[{"start":{"date-parts":[[2016,7,20]],"date-time":"2016-07-20T00:00:00Z","timestamp":1468972800000},"content-version":"vor","delay-in-days":201,"URL":"http:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"COST (European Cooperation in Science and Technology)"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016]]},"DOI":"10.1145\/2908812.2908892","type":"proceedings-article","created":{"date-parts":[[2016,7,27]],"date-time":"2016-07-27T15:32:51Z","timestamp":1469633571000},"page":"77-84","source":"Crossref","is-referenced-by-count":1,"title":["Artificial Immune Systems can Beat Evolutionary Algorithms in Combinatorial Optimisation"],"prefix":"10.1145","author":[{"given":"Benjamin","family":"Doerr","sequence":"first","affiliation":[{"name":"\u00c9cole Polytechnique, Univ. Paris-Saclay, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Thomas","family":"Jansen","sequence":"additional","affiliation":[{"name":"Aberystwyth University, Aberystwyth, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Christine","family":"Zarges","sequence":"additional","affiliation":[{"name":"University of Birmingham, Birmingham, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","reference":[{"key":"key-10.1145\/2908812.2908892-1","doi-asserted-by":"crossref","unstructured":"E. Clark, A. Hone, and J. Timmis. A Markov chain model of the B-cell algorithm. In Proceedings of the 4th International Conference on Artificial Immune Systems (ICARIS 2005), pages 318--330. Springer, 2005.","DOI":"10.1007\/11536444_24"},{"key":"key-10.1145\/2908812.2908892-2","doi-asserted-by":"crossref","unstructured":"D. Corus, J. He, T. Jansen, P. S. Oliveto, D. Sudholt, and C. Zarges. On easiest functions for somatic contiguous hypermutations and standard bit mutations. In Proceedings of the 17th Annual Conference on Genetic and Evolutionary Computation (GECCO 2015), pages 1399--1406. ACM, 2015.","DOI":"10.1145\/2739480.2754799"},{"key":"key-10.1145\/2908812.2908892-3","doi-asserted-by":"crossref","unstructured":"V. Cutello, G. Nicosia, and M. Pavone. Exploring the capability of immune algorithms: A characterization of hypermutation operators. In Proceedings of the 3rd International Conference on Artificial Immune Systems (ICARIS 2004), pages 263--276. Springer, 2004.","DOI":"10.1007\/978-3-540-30220-9_22"},{"key":"key-10.1145\/2908812.2908892-4","doi-asserted-by":"crossref","unstructured":"V. Cutello, G. Nicosia, M. Romeo, and P. S. Oliveto. On the convergence of immune algorithms. In Proceedings of the 1st Symposium on Foundations of Computational Intelligence (FOCI 2007), pages 409--415. IEEE, 2007.","DOI":"10.1109\/FOCI.2007.371504"},{"key":"key-10.1145\/2908812.2908892-5","unstructured":"L. N. de Castro and J. Timmis. Artificial Immune Systems: A New Computational Intelligence Approach. Springer, 2002."},{"key":"key-10.1145\/2908812.2908892-6","doi-asserted-by":"crossref","unstructured":"L. N. de Castro and F. J. Von Zuben. Learning and optimization using the clonal selection principle. IEEE Transactions on Evolutionary Computation, 6(3):239--251, 2002.","DOI":"10.1109\/TEVC.2002.1011539"},{"key":"key-10.1145\/2908812.2908892-7","doi-asserted-by":"crossref","unstructured":"S. Droste, T. Jansen, and I. Wegener. On the analysis of the (1+1) evolutionary algorithm. Theoretical Computer Science, 276(1--2):51--81, 2002.","DOI":"10.1016\/S0304-3975(01)00182-7"},{"key":"key-10.1145\/2908812.2908892-8","doi-asserted-by":"crossref","unstructured":"O. Giel and I. Wegener. Evolutionary algorithms and the maximum matching problem. In Proceedings of the 20th Annual Symposium on Theoretical Aspects of Computer Science (STACS 2003), pages 415--426. Springer, 2003.","DOI":"10.1007\/3-540-36494-3_37"},{"key":"key-10.1145\/2908812.2908892-9","doi-asserted-by":"crossref","unstructured":"C. Horoba, T. Jansen, and C. Zarges. Maximal age in randomized search heuristics with aging. In Proceedings of the 11th Genetic and Evolutionary Computation Conference (GECCO 2009), pages 803--810. ACM, 2009.","DOI":"10.1145\/1569901.1570012"},{"key":"key-10.1145\/2908812.2908892-10","doi-asserted-by":"crossref","unstructured":"T. Jansen. Analyzing Evolutionary Algorithms. The Computer Science Perspective. Springer, 2013.","DOI":"10.1007\/978-3-642-17339-4"},{"key":"key-10.1145\/2908812.2908892-11","doi-asserted-by":"crossref","unstructured":"T. Jansen, P. S. Oliveto, and C. Zarges. On the analysis of the immune-inspired B-cell algorithm for the vertex cover problem. In Proceedings of the 10th International Conference on Artificial Immune Systems (ICARIS 2011), pages 117--131. Springer, 2011.","DOI":"10.1007\/978-3-642-22371-6_13"},{"key":"key-10.1145\/2908812.2908892-12","doi-asserted-by":"crossref","unstructured":"T. Jansen and I. Wegener. Evolutionary algorithms | how to cope with plateaus of constant fitness and when to reject strings of the same fitness. IEEE Transactions on Evolutionary Computation, 5(6):589--599, 2002.","DOI":"10.1109\/4235.974841"},{"key":"key-10.1145\/2908812.2908892-13","doi-asserted-by":"crossref","unstructured":"T. Jansen and C. Zarges. Analyzing different variants of immune inspired somatic contiguous hypermutations. Theoretical Computer Science, 412(6):517--533, 2011.","DOI":"10.1016\/j.tcs.2010.09.027"},{"key":"key-10.1145\/2908812.2908892-14","doi-asserted-by":"crossref","unstructured":"T. Jansen and C. Zarges. On benefits and drawbacks of aging strategies for randomized search heuristics. Theoretical Computer Science, 412(6):543--559, 2011.","DOI":"10.1016\/j.tcs.2010.03.032"},{"key":"key-10.1145\/2908812.2908892-15","doi-asserted-by":"crossref","unstructured":"T. Jansen and C. Zarges. On the role of age diversity for effective aging operators. Evolutionary Intelligence, 4(2):99--125, 2011.","DOI":"10.1007\/s12065-011-0051-6"},{"key":"key-10.1145\/2908812.2908892-16","doi-asserted-by":"crossref","unstructured":"T. Jansen and C. Zarges. Variation in artificial immune systems: Hypermutations with mutation potential. In Proceedings of the 10th International Conference on Artificial Immune Systems (ICARIS 2011), pages 132--145. Springer, 2011.","DOI":"10.1007\/978-3-642-22371-6_14"},{"key":"key-10.1145\/2908812.2908892-17","doi-asserted-by":"crossref","unstructured":"T. Jansen and C. Zarges. Computing longest common subsequences with the B-cell algorithm. In Proceedings of the 11th International Conference on Artificial Immune Systems (ICARIS 2012), pages 111--124. Springer, 2012.","DOI":"10.1007\/978-3-642-33757-4_9"},{"key":"key-10.1145\/2908812.2908892-18","doi-asserted-by":"crossref","unstructured":"T. Jansen and C. Zarges. Reevaluating immune-inspired hypermutations using the fixed budget perspective. IEEE Transactions Evolutionary Computation, 18(5):674--688, 2014.","DOI":"10.1109\/TEVC.2014.2349160"},{"key":"key-10.1145\/2908812.2908892-19","unstructured":"T. Jansen and C. Zarges. Understanding randomised search heuristics. Lessons from the evolution of theory: A case study. In Proceedings of the 20th International Conference on Soft Computing (MENDEL 2014), pages 293--298, 2014."},{"key":"key-10.1145\/2908812.2908892-20","doi-asserted-by":"crossref","unstructured":"T. Jansen and C. Zarges. Analysis of randomised search heuristics for dynamic optimisation. Evolutionary Computation, 23(4):513--541, 2015.","DOI":"10.1162\/EVCO_a_00164"},{"key":"key-10.1145\/2908812.2908892-21","doi-asserted-by":"crossref","unstructured":"J. Kelsey and J. Timmis. Immune inspired somatic contiguous hypermutations for function optimisation. In Proceedings of the 5th Genetic and Evolutionary Computation Conference (GECCO 2003), pages 207--218. Springer, 2003.","DOI":"10.1007\/3-540-45105-6_26"},{"key":"key-10.1145\/2908812.2908892-22","unstructured":"J. Kleinberg and E. Tardos. Algorithm Design. Pearson, 2005."},{"key":"key-10.1145\/2908812.2908892-23","doi-asserted-by":"crossref","unstructured":"R. Motwani and P. Raghavan. Randomized Algorithms. Cambridge University Press, 1995.","DOI":"10.1017\/CBO9780511814075"},{"key":"key-10.1145\/2908812.2908892-24","doi-asserted-by":"crossref","unstructured":"P. S. Oliveto and D. Sudholt. On the runtime analysis of stochastic ageing mechanisms. In Proceedings of the 16th Genetic and Evolutionary Computation Conference (GECCO 2014), pages 113--120. ACM, 2014.","DOI":"10.1145\/2576768.2598328"},{"key":"key-10.1145\/2908812.2908892-25","doi-asserted-by":"crossref","unstructured":"A. M. Sutton. Superpolynomial lower bounds for the (1+1) EA on some easy combinatorial problems. In Proceedings of the 16th Genetic and Evolutionary Computation Conference (GECCO 2014), pages 1431--1438. ACM, 2014.","DOI":"10.1145\/2576768.2598278"},{"key":"key-10.1145\/2908812.2908892-26","doi-asserted-by":"crossref","unstructured":"C. Witt. Tight bounds on the optimization time of a randomized search heuristic on linear functions. Combinatorics, Probability & Computing, 22(2):294--318, 2013.","DOI":"10.1017\/S0963548312000600"},{"key":"key-10.1145\/2908812.2908892-27","doi-asserted-by":"crossref","unstructured":"C. Zarges. Rigorous runtime analysis of inversely fitness proportional mutation rates. In Proceedings of the 10th International Conference on Parallel Problem Solving from Nature (PPSN 2008), pages 112--122. Springer, 2008.","DOI":"10.1007\/978-3-540-87700-4_12"},{"key":"key-10.1145\/2908812.2908892-28","doi-asserted-by":"crossref","unstructured":"C. Zarges. On the utility of the population size for inversely fitness proportional mutation rates. In Proceedings of the 10th Conference on Foundations of Genetic Algorithms (FOGA 2009), pages 39--46. ACM, 2009.","DOI":"10.1145\/1527125.1527132"}],"event":{"number":"2016","sponsor":["SIGEVO, ACM Special Interest Group on Genetic and Evolutionary Computation"],"acronym":"GECCO '16","name":"the 2016","start":{"date-parts":[[2016,7,20]]},"location":"Denver, Colorado, USA","end":{"date-parts":[[2016,7,24]]}},"container-title":["Proceedings of the 2016 on Genetic and Evolutionary Computation Conference - GECCO '16"],"original-title":[],"deposited":{"date-parts":[[2019,9,11]],"date-time":"2019-09-11T20:15:36Z","timestamp":1568232936000},"score":1,"resource":{"primary":{"URL":"http:\/\/dl.acm.org\/citation.cfm?doid=2908812.2908892"}},"subtitle":[],"proceedings-subject":"Genetic and Evolutionary Computation Conference","short-title":[],"issued":{"date-parts":[[2016]]},"references-count":28,"URL":"https:\/\/doi.org\/10.1145\/2908812.2908892","relation":{},"subject":[],"published":{"date-parts":[[2016]]}}}