Abstract
We investigate the effects of precision on the efficiency of various local search algorithms on 1-D unimodal functions. We present a (1+1)-EA with adaptive step size which finds the optimum in O(log n) steps, where n is the number of points used. We then consider binary (base-2) and reflected Gray code representations with single bit mutations. The standard binary method does not guarantee locating the optimum, whereas using the reflected Gray code does so in Θ((log n)2) steps. A(1+1)-EA with a fixed mutation probability distribution is then presented which also runs in O((log n)2). Moreover, a recent result shows that this is optimal (up to some constant scaling factor), in that there exist unimodal functions for which a lower bound of Ω((log n)2) holds regardless of the choice of mutation distribution. For continuous multimodal functions, the algorithm also locates the global optimum in O((log n)2). Finally, we show that it is not possible for a black box algorithm to efficiently optimise unimodal functions for two or more dimensions (in terms of the precision used).
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Kiefer, J.: Sequential minimal search for a maximum. Proc. Am. Math. Soc. 4, 502–506 (1953)
Goldstein, A.S., Reingold, E.M.: A Fibonnacci version of Kraft’s inequality applied to discrete unimodal search. SIAM J. Comput. 22, 751–777 (1993)
Dietzfelbinger, M., Rowe, J.E., Wegener, I., Woelfel, P.: Tight bounds for blind search on the integers. In: Proc. 25th International Symposium on Theoretical Aspects of Computer Science, pp. 241–252 (2008)
Whitley, L.D., Rowe, J.E.: Gray, binary and real valued encodings: quad search and locality proofs. In: Wright, A.H., Vose, M.D., De Jong, K., Schmitt, L. (eds.) Foundations of Genetic Algorithms, vol. 8. LNCS, vol. 3469, pp. 21–36. Springer, Berlin (2005)
Whitley, L.D.: A free lunch proof for Gray versus binary encodings. In: Banzhaf, W., et al. (ed.) GECCO 1999, pp. 726–733. Morgan Kaufmann, Los Altos (1999)
Rowe, J.E., Whitley, L.D., Barbulescu, L., Watson, J.-P.: Properties of Gray and binary representations. Evol. Comput. 12(1), 47–76 (2004)
Dietzfelbinger, M., Rowe, J.E., Wegener, I., Woelfel, P.: Precision, local search and unimodal functions. In: Ryan, C., Keijzer, M. (eds.) GECCO 2008, pp. 771–778. ACM, New York (2008)
Rowe, J.E., Hidović, D.: An evolution strategy using a continuous version of the gray-code neighbourhood distribution. In: Deb, K. (ed.) GECCO 2004. LNCS, vol. 3102, pp. 725–736. Springer, Berlin (2004)
Hidović, D., Rowe, J.E.: Validating a model of colon colouration using an evolution strategy with adaptive approximations. In: Deb, K. (ed.) GECCO 2004. LNCS, vol. 3102, pp. 1005–1016. Springer, Berlin (2004)
Jägersküpper, J.: Oblivious randomized direct search for real-parameter optimization. In: Proceedings of the 16th European Symposium on Algorithms (ESA 2008). LNCS, vol. 5193, pp. 553–564. Springer, Berlin (2008)
Mathur, A., Reingold, E.M.: Generalized Kraft’s inequality and discrete k-modal search. SIAM J. Comput. 25, 420–447 (1996)
Droste, S., Jansen, T., Wegener, I.: On the optimization of unimodal functions with the (1+1) evolutionary algorithm. In: Proc. 5th International Conference on Parallel Problem Solving from Nature. LNCS, vol. 1498, pp. 13–22. Springer, Berlin (1998)
Wegener, I.: Complexity Theory: Exploring the Limits of Efficient Algorithms. Springer, Berlin (2005)
Jägersküpper, J.: Algorithmic analysis of a basic evolutionary algorithm for continuous optimization. Theor. Comput. Sci. 279, 329–347 (2007)
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It was with great sorrow that we learned of the death of Ingo Wegener on 26 November 2008. Ingo brought the rest of us together to work on this problem. He is greatly missed by us all.
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Dietzfelbinger, M., Rowe, J.E., Wegener, I. et al. Precision, Local Search and Unimodal Functions. Algorithmica 59, 301–322 (2011). https://doi.org/10.1007/s00453-009-9352-x
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DOI: https://doi.org/10.1007/s00453-009-9352-x