Abstract
This chapter presents the switch analysis approach for analyzing the running time complexity of evolutionary algorithms. Switch analysis works by comparing two optimization processes, thus can help analyze a complicated optimization process by comparing with a simpler reference process. It is applied to prove the expected running time lower bound of mutation-based EAs on the pseudo-Boolean function class with a unique global optimal solution.
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© 2019 Springer Nature Singapore Pte Ltd.
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Zhou, ZH., Yu, Y., Qian, C. (2019). Running Time Analysis: Switch Analysis. In: Evolutionary Learning: Advances in Theories and Algorithms. Springer, Singapore. https://doi.org/10.1007/978-981-13-5956-9_4
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DOI: https://doi.org/10.1007/978-981-13-5956-9_4
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Publisher Name: Springer, Singapore
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Online ISBN: 978-981-13-5956-9
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