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Heuristic Optimization

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Encyclopedia of Systems Biology

Definition

Heuristic designates a computational procedure that determines an optimal solution by iteratively trying to improve a candidate solution with regard to a given measure of quality. Heuristics make few or no assumptions about the problem being optimized and can search large spaces of candidate solutions toward finding optimal or near-optimal solutions at a reasonable computational cost without being able to guarantee either feasibility or optimality, or even in many cases to state how close to optimality a particular feasible solution is. Heuristics implement some form of stochastic search optimization, such as evolution programming, evolution strategy, genetic algorithms, genetic programming, and differential evolution (Michalewicz 1996; Reeves 1995; Sharda et al. 2003; Zhilinskas and Žilinskas 2008). Other methods having a similar meaning as heuristic are derivative-free, direct search, and black-box optimization techniques.

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Heuristic optimization algorithms...

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References

  • Michalewicz Z (1996) Genetic algorithms + data structures = evolution programs. Springer, Berlin

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  • Reeves CR (1995) Modern heuristic techniques for combinatorial problems. McGraw-Hill, Londres

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  • Sharda R, Voß S, Woodruff DL, Fink A (2003) Optimization software class libraries. Springer, New York, pp 81–154

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  • Zhilinskas A, Žilinskas A (2008) Stochastic global optimization. Springer, New York

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Correspondence to Feng-Sheng Wang .

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Wang, FS., Chen, LH. (2013). Heuristic Optimization. In: Dubitzky, W., Wolkenhauer, O., Cho, KH., Yokota, H. (eds) Encyclopedia of Systems Biology. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-9863-7_411

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