Projects per year
Hybrid and mixed strategy EAs have become rather popular for tackling various complex and NP-hard optimization problems. While empirical evidence suggests that such algorithms are successful in practice, rather little theoretical support for their success is available, not mentioning a solid mathematical foundation that would provide guidance towards an efficient design of this type of EAs. In the current paper we develop a rigorous mathematical framework that suggests such designs based on generalized schema theory, fitness levels and drift analysis. An example-application for tackling one of the classical NP-hard problems, the "single-machine scheduling problem" is presented.
|Title of host publication||2013 IEEE Congress on Evolutionary Computation|
|Publication status||Published - 01 Jun 2013|
|Event||2013 IEEE Congress on Evolutionary Computation (CEC) - Cancun, Mexico|
Duration: 20 Jun 2013 → 23 Jun 2013
|Conference||2013 IEEE Congress on Evolutionary Computation (CEC)|
|Period||20 Jun 2013 → 23 Jun 2013|
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- 1 Finished
Evolutionary Approximation Algorithms for Optimization: Algorithm design and Complexity Analysis
Engineering and Physical Sciences Research Council
01 May 2011 → 31 Oct 2015
Project: Externally funded research