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As one of the most popular and successful methods in industrial applications, model predictive control (MPC) has attracted increasing interest in the past two decades. However, one of open issues in this research filed is how to solve the constrained nonlinear optimization problems in MPC. From the perspective of evolutionary algorithm, this paper presents a novel population extremal optimization...
Genetic-fuzzy mining (GFM) was proposed to train fuzzy membership functions, thus enhancing the final solution quality. However, it is quite time-consuming because of frequent database scans for fitness evaluation. In this paper, we propose a parallel algorithm with MapReduce architecture to further speed up the genetic-fuzzy mining process. In the proposed approach, the master processor randomly...
Multi-population-based bio-inspired computation may use migration among groups to increase the search diversity. Through good solutions exchanged among sub-populations, better solutions may be found with a high probability. In this paper, we propose two algorithms to dynamically adjust the two primary parameters, migration interval and migration rate, for flexibly reflect solution situation for effective...
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