A comprehensive survey of fitness approximation in evolutionary computation
Yaochu Jin: A comprehensive survey of fitness approximation in evolutionary computation. Soft Computing journal, vol 9, pp. 3-12, 2005.
Evolutionary algorithms (EAs) have received increasing interests both in the academy and industry. One main difficulty in applying EAs to real-world appli- cations is that EAs usually need a large number of fitness evaluations before a satisfying result can be obtained. However, fitness evaluations are not always straightfor- ward in many real-world applications. Either an explicit fitness function does not exist, or the evaluation of the fitness is computationally very expensive. In both cases, it is necessary to estimate the fitness function by con- structing an approximate model. In this paper, a com- prehensive survey of the research on fitness approxima- tion in evolutionary computation is presented. Main is- sues like approximation levels, approximate model man- agement schemes, model construction techniques are re- viewed. To conclude, open questions and interesting is- sues in the field are discussed.
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