this paper, presents a suitable control system to manage energy in distributed power generation system with a battery energy storage station and fuel cell. first, proper dynamic shape modeling is prepared. second, control system is proposed which is based on classic controller. this model is educated with genetic algorithm and particle swarm optimization. the proposed strategy is compared with ...

in this paper, a new genetic algorithm (ga) is presented for solving the multi-mode resource-constrained project scheduling problem (mrcpsp) with minimization of project makespan as the objective subject to resource and precedence constraints. a random key and the related mode list (ml) representation scheme are used as encoding schemes and the multi-mode serial schedule generation scheme (mssg...

clustering is one of the known techniques in the field of data mining where data with similar properties is within the set of categories. k-means algorithm is one the simplest clustering algorithms which have disadvantages sensitive to initial values of the clusters and converging to the local optimum. in recent years, several algorithms are provided based on evolutionary algorithms for cluster...

In this paper, the gain in LD-CELP speech coding algorithm is predicted using three neural models, that are equipped by genetic and particle swarm optimization (PSO) algorithms to optimize the structure and parameters of neural networks. Elman, multi-layer perceptron (MLP) and fuzzy ARTMAP are the candidate neural models. The optimized number of nodes in the first and second hidden layers of El...

With the formation of the competitive electricity markets in the world, optimization of bidding strategies has become one of the main discussions in studies related to market designing. Market design is challenged by multiple objectives that need to be satisfied. The solution of those multi-objective problems is searched often over the combined strategy space, and thus requires the simultaneous...

imperialist competitive algorithm (ica) is a new socio-politically motivated global search strategy. the ica is applied to hybrid composite laminates to obtain minimum weight and cost. the approach which is chosen for conducting the multi-objective optimization was the weighted sum method (wsm). the hybrid composite laminates are made of glass/epoxy and carbon/epoxy to combine the lightness and...

In this paper, an immune genetic based algorithm (IGA) for random test pattern generation was proposed. Genetic algorithms (GA) solve many search and optimization problems, effectively. However, they may drop into local optimal solutions; or they may find the optimal solution by low convergence speed. To overcome these problems, we used the immune concept and GA algorithm for random-based test ...

Reader network planning (RNP) problem of radio frequency identification (RFID) system is a combinational optimization problem. In this study, we propose a genetic algorithm (GA) to solve this RNP problem. We have tested the proposed GA on several RNP problems and compare with a particle swarm optimization (PSO) method by solving the same RNPs. The comparison results demonstrate that the propose...

In order to enhance the global and local search ability of genetic algorithm (GA) in solution space, an improved GA is introduced in this paper. First, the chaotic initialization is introduced into GA to improve its global search performance. Furthermore, improved quantum crossover is introduced to exchange information between different chromosomes, this action is useful for improving local sea...

In this paper we propose an efficient offline job scheduling algorithm working in a grid environment that is based on a relatively new evolutionary metaheuristic called generalized extremal optimization (GEO). We compare our experimental results with those obtained using a very popular evolutionary metaheuristic, the genetic algorithm (GA). The scheduling algorithm implies two-stage scheduling....