Abstract
This chapter studies the easiest and hardest instances of a problem class respect to the given evolutionary algorithm, for the understanding of the algorithm. Through the derived theorem, the easiest and hardest functions in the pseudo-Boolean function class with a unique global optimal solution are identified for (1+1)-EA with any mutation probability less than 0.5.
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© 2019 Springer Nature Singapore Pte Ltd.
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Zhou, ZH., Yu, Y., Qian, C. (2019). Boundary Problems of EAs. In: Evolutionary Learning: Advances in Theories and Algorithms. Springer, Singapore. https://doi.org/10.1007/978-981-13-5956-9_7
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DOI: https://doi.org/10.1007/978-981-13-5956-9_7
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Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-5955-2
Online ISBN: 978-981-13-5956-9
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