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We propose a new archive-based steady-state micro genetic algorithm (ASMiGA). In this context, a new archive maintenance strategy is proposed, which maintains a set of nondominated solutions in the archive unless the archive size falls below a minimum allowable size. It makes the archive size adaptive and dynamic. We have proposed a new environmental selection strategy and a new mating selection strategy...
In this paper, we have proposed a fuzzy interval time series model using a new strategy to replace the conventional defuzzification step, where genetic algorithm has been used to optimize the interval parameters and neural network has been used to learn the trend of the time series. First order fuzzy time series with equal time interval has been used on two data sets, enrollments of the University...
In this paper we have proposed a new archive based steady state multi-objective genetic algorithm, which performs well, especially in higher dimensional space. An improved archive maintenance strategy has been introduced in this algorithm which is adaptive as well as dynamic in size. The archive maintenance strategy tries to maintain only the set of nondominated solutions in the archive. However,...
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