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Erschienen in:
2009 | OriginalPaper | Buchkapitel
Why Is Optimization Difficult?
verfasst von : Thomas Weise, Michael Zapf, Raymond Chiong, Antonio J. Nebro
Erschienen in: Nature-Inspired Algorithms for Optimisation
Verlag: Springer Berlin Heidelberg
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This chapter aims to address some of the fundamental issues that are often encountered in optimization problems, making them difficult to solve. These issues include premature convergence, ruggedness, causality, deceptiveness, neutrality, epistasis, robustness, overfitting, oversimplification, multi-objectivity, dynamic fitness, the No Free Lunch Theorem, etc. We explain why these issues make optimization problems hard to solve and present some possible countermeasures for dealing with them. By doing this, we hope to help both practitioners and fellow researchers to create more efficient optimization applications and novel algorithms.