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An opposition learning multi-objective genetic algorithm based multi-objective optimization approach of rolling schedules for tandem hot rolling is proposed. According to actual rolling process, the power distribution and rolling energy consumption are selected as cost functions. Then the multi-objective model of rolling schedules is established. The opposition learning multi-objective genetic algorithm...
Because have very high ability of overall situation searching and convergence speed, show excellently in keeping solution variety, the niche genetic algorithm(NGA) is widely used to solving various kinds of combination optimization problem, but the traditional niche genetic algorithm(T-GA) have the problem that the discrimination standard of Euclidean distance between two individuals is not development...
Immune Genetic Algorithm-based Load Balancing (IGALB) was proposed to improve the efficiency of search quality and the poor performance of local search in the Simple Genetic Algorithm-based Load Balancing (SGALB). This algorithm ensured the diversity of population and overcame the SGALB premature convergence by carrying out the affinity and concentration calculations. Meanwhile under certain conditions...
Large-scale global optimization (LSGO) is a very important and challenging task in optimization domain, which is embedded in many scientific and engineering applications. Previously, the cooperative co-evolution (CC) is a usual and effective choice for LSGO problems. In this paper, aim at more fully exploring the flexibility and potential of CC strategy, an adaptive CC (ACC) is designed to handle...
The multiple origins multiple destinations routing (MOMDR) problem becomes extremely complicated when considering the traffic volumes on road sections. When solving this kind of problem, only heuristic algorithms have practical values because it is a typical NP-Hard problem. This paper applies Genetic Algorithm (GA) to enhance Sorting-Randomizing-Adjusting-Updating (SRAU) algorithm. The previous paper...
Aiming at the difficulty of designing weighting matrices for linear quadratic regulator (LQR), a multi-objective evolution algorithm (MOEA) based approach is proposed. The LQR weighting matrices, state feedback control rate and optimal controller are obtained by means of establishing the multi-objective optimization model of LQR weighting matrices and applying MOEA to it, which makes control system...
Its deficiency was revealed because of traffic pattern identification method of elevator group control system based on using BP neural network, and a new traffic patten identification model is proposed which is based on optimizing fuzzy neural network by genetic algorithm. The genetic algorithm is used to train fuzzy BP neural network, which can overcome the shortcoming of local minimum appeared while...
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