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Solving Constrained Optimization Problems (COPs) is challenging task in the field of computer optimization. Many researchers have put efforts to solve COPs using techniques such as Dynamic Programming, Non Linear Programming etc. These methods are generally trapped in local optima. The solution to this lacuna is Evolutionary Algorithms (EAs), which work as a promising technique for wide range of Constrained...
Adapting genetic operators and parameter settings during the optimization process can improve the overall performance of evolutionary algorithms (EAs). In this paper, a novel maturity-based adaptation strategy for EAs is proposed. During the search process, a maturity degree of the population is calculated based on both the population distribution in the search space and that in the fitness space...
This paper proposes a new circuit design optimization method where Genetic Algorithm (GA) with parameterized uniform crossover (GApuc) is combined with Taguchi method. The purposed are (a) using Taguchi method to search for optimal fitness value and (b) evaluating the power and signal delay of logic blocks in circuit design to get an optimum circuit in complexity, power and signal delay. The present...
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