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Author Thierens, Dirk
Source CiteSeerX
Content type Text
File Format PDF
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Simple Genetic Algorithm ♦ Scalability Problem ♦ Competent Genetic Algorithm ♦ Scalable Evolutionary Computation ♦ Problem Size ♦ Clear Insight ♦ Problem-coding Structure ♦ Algorithmic Design ♦ Research Topic ♦ Ga Parameter Space ♦ Block Mixing ♦ Building Block ♦ Recent Year ♦ Sweet Spot ♦ Important Issue ♦ Schema Theorem
Abstract Scalable evolutionary computation has become an intensively studied research topic in recent years. The issue of scalability is predominant in any eld of algorithmic design, but it became particularly relevant for the design of competent genetic algorithms once the scalability problems of simple genetic algorithms were understood. Here we present some of the work that has aided in getting a clear insight in the scalability problems of simple genetic algorithms. Particularly, we discuss the important issue of building block mixing and show how the need for mixing places a boundary in the GA parameter space that together with the boundary from the schema theorem delimits the region where the GA converges reliably to the optimum of problems of bounded diculty. This region - or sweet spot as it has been called - shrinks unfortunately very rapidly with increasing problem size unless the building blocks are tightly linked in the problem-coding structure. In addition we look how straightforw...
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Publisher Date 1999-01-01