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In order to overcome premature phenomenon of simple genetic algorithms and inability to optimize algorithms with complex constraints, an improved genetic algorithms based on some improved methods is presented in this paper and is applied in optimization design of frame structure by adopting adaptive crossover rate and mutation rate, adjusting population size, fitness and penalty function and elitist...
Neural network often is trained by multilayer feedforward neural network ago, but it may fall into local minimum point. In this article, swarm optimization particle is improved so that it can adapt to solve optimization problem of discrete variables. At the same time, introducing the crossover operation of genetic algorithm make it form hybrid particle swarm optimization. Then combining the method...
Biogeography-Based Optimization (BBO) is a new bio-inspired and population based optimization algorithm. The convergence of original BBO to the optimum value is slow. Intelligent Biogeography-Based Optimization (IBBO) technique is a hybrid version of BBO with Bacterial Foraging algorithm (BFA). In this paper, authors integrate the bacterial intelligence feature of BFA to decide the valid emigration...
Water network rehabilitation is a complex problem, and many facets should be concerned in the solving process. It is a discrete variables, non-linear, multi-objective optimal problem. An optimization approach is discussed in this paper by transforming the hydraulic constraints into objective functions of optimization model of water supply network rehabilitation problem. The non-dominated sorting Genetic...
In this paper, a hybrid optimization technique, in which immune genetic algorithm is combined with interior point method, is proposed for solving the dynamic reactive power optimization problem. The switching time limits of shunt capacitors and transformer tap ratios, which make the problem to be dynamic, are only related with discrete variables. In the proposed hybrid method, the immune genetic algorithm...
One of the most important practical considerations in the optimization of discrete structures is that the structural members are generally to be selected from available profiles list. Genetic algorithm shows certain advantages over other classical optimization procedures in structural optimization of discrete variables. In this paper we introduce the idea of directed mutation into the simple genetic...
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