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Level-Dependent Experimental Optimization

lliya Bluskov1
1 Department of Mathematics and Computer Science University of Northern British Columbia Prince George, B.C., Canada V2N 4Z9

Abstract

In this paper, we discuss a self-adjusting and self-improving combinatorial optimization algorithm. Variations of this algorithm have been successfully applied in recent research in Design Theory. The approach is simple but general and can be applied in any instance of a combinatorial optimization problem.