the imperialist competitive algorithm (ica) that was recently introduced has shown its good performance in optimization problems. this algorithm is inspired by competition mechanism among imperialists and colonies, in contrast to evolutionary algorithms. this paper presents optimization of bead geometry in welding process using of ica. therefore, two case studies from literature are presented t...

the purpose of this paper is multi-objective optimization of refrigeration cycle by optimization of all components of the cycle contains heat exchangers, air condenser, evaporator and super-heater. studied refrigeration cycle is compression refrigeration cycle of unit 132 third refineries in south pars that provide chilled water for cooling refinery equipment's. cycle will be performed by ...

In this paper, we present an application of evolved neural networks using a real coded genetic algorithm for simulations of monthly groundwater levels in a coastal aquifer located in the Shabestar Plain, Iran. After initializing the model with groundwater elevations observed at a given time, the developed hybrid genetic algorithm-back propagation (GA-BP) should be able to reproduce groundwater ...

among various heuristics techniques, genetic algorithm (ga) is one of the most widely used techniques which has successfully been applied on a variety of complex combinatorial problems. the performance of ga largely depends on the proper selection of its parameters values; including crossover mechanism, probability of crossover, population size and mutation rate and selection percent. in this p...

In this paper the Phase-Matching bandwidth, effective nonlinear coefficient and the walk-off angle within the effective bandwidth of the LiGa(SexS1-x)2 biaxial nonlinear crystals are calculated using the Genetic algorithm (GA). This calculation is held for all tree principle XY, YZ and XZ planes individually. The results are shown the accuracy of the applied algorithm is quite qualified.

A hybrid genetic scheduling strategy (H-GA) is described in this article, H-GA combines with grouping and load balancing strategy based on traditional genetic algorithm (GA). First, tasks are divided into several different subgroups by task granularity. Then, task subgroup which is selected by granularity from big to small is used to schedule by the genetic algorithm, and during scheduling, the...

The concepts of robust classification and intelligently controlling the search process of genetic algorithm (GA) are introduced and integrated with a conventional genetic classifier for development of a new version of it, which is called Intelligent and Robust GA-classifier (IRGA-classifier). It can efficiently approximate the decision hyperplanes in the feature space. It is shown experime...

Genetic algorithm (GA), as an important intelligence computing tool, is a wide research content in the application domain and the academic circle now. This paper elaborates the improvement of premature convergence in GA used for optimizing multimodal numerical problems. Mutation is the principle operation in Genetic Algorithm (GA) for enhancing the degree of population diversity, but it is prov...