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Upper Bounds on the Time and Space Complexity of Optimizing Additively Separable Functions

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Book cover Genetic and Evolutionary Computation – GECCO 2004 (GECCO 2004)

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Abstract

We present upper bounds on the time and space complexity of finding the global optimum of additively separable functions, a class of functions that has been studied extensively in the evolutionary computation literature. The algorithm presented uses efficient linkage discovery in conjunction with local search. Using our algorithm, the global optimum of an order-k additively separable function defined on strings of length ℓ can be found using O(ℓ ln(ℓ)2k) function evaluations, a bound which is lower than all those that have previously been reported.

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References

  1. Goldberg, D.E.: The Design of Innovation: Lessons from and for competent genetic algorithms. Kluwer Academic Publishers, Boston (2002)

    MATH  Google Scholar 

  2. Goldberg, D.E., Deb, K., Kargupta, H., Harik, G.: Rapid, accurate optimization of difficult problems using fast messy genetic algorithms. In: Proc. Fifth Int’l. Conf. on Genetic Algorithms, pp. 56–64 (1993)

    Google Scholar 

  3. Harik, G.R., Goldberg, D.E.: Learning linkage through probabilistic expression. Computer Methods in Applied Mechanics and Engineering 186(2-4), 295–310 (2000)

    Article  MATH  Google Scholar 

  4. Heckendorn, R.B., Wright, A.H.: Efficient linkage discovery by limited probing. In: Proc. 2003 Genetic and Evolutionary Computation Conf., pp. 1003–1014 (2003)

    Google Scholar 

  5. Kauffman, S.A.: The Origins of Order. Oxford University Press, New York (1993)

    Google Scholar 

  6. Larrañaga, P., Lozano, J.A.: Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation. Kluwer Academic Publishers, Boston (2001)

    Google Scholar 

  7. Munemoto, M., Goldberg, D.E.: Linkage identification by non-monotonicity detection for overlapping functions. Evolutionary Computation 7(4), 377–398 (1999)

    Article  Google Scholar 

  8. Pelikan, M.: Bayesian Optimization Algorithm: From Single Level to Hierarchy. Ph.D thesis, University of Illinois Urbana-Champaign (2002)

    Google Scholar 

  9. Pelikan, M., Goldberg, D.E., Cantú-Paz, E.: Linkage problem, distribution estimation, and Bayesian networks. Evolutionary Computation 8(3), 311–340 (2000)

    Article  Google Scholar 

  10. Weinberger, E.D.: NP completeness of Kauffman’s NK model, a tunable rugged fitness landscape. Santa Fe Institute T.R. 96-02-003 (1996)

    Google Scholar 

  11. Streeter, M.J.: http://www.cs.cmu.edu/~matts/gecco_2004/index.html

  12. Wright, H., Heckendorn, R.B.: Personal communication (January 2004)

    Google Scholar 

  13. Wright, H., Thompson, R.K., Zhang, J.: The computational complexity of N-K fitness functions. IEEE Transactions on Evolutionary Computation 4(4), 373–379 (2000)

    Article  Google Scholar 

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Streeter, M.J. (2004). Upper Bounds on the Time and Space Complexity of Optimizing Additively Separable Functions. In: Deb, K. (eds) Genetic and Evolutionary Computation – GECCO 2004. GECCO 2004. Lecture Notes in Computer Science, vol 3103. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24855-2_17

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  • DOI: https://doi.org/10.1007/978-3-540-24855-2_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22343-6

  • Online ISBN: 978-3-540-24855-2

  • eBook Packages: Springer Book Archive

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