نتایج جستجو برای: dominant sorting genetic algorithm
تعداد نتایج: 1441000 فیلتر نتایج به سال:
The design of three-phase induction motors is a challenge in electrical engineering. Therefore, new design techniques are continuously provided. Since the design of the induction motors is carried out for different purposes, it is difficult to find a method that can addresses all the targets. Nowadays, the normal methods used to solve multi-objective problems are the optimization strategies. In...
this study emphasized the ability of genetic algorithm and cellular automate to simulate urban land use changes by integrating adaptive model. the most important part of modeling is to define transition rules. in this research, a cellular automata model in dinamica ego software was used coupled with genetic algorithm. according to disability of the software for manipulating large number of var...
Based on the analysis on the basic principles and characteristics of the existing multiobjective genetic algorithm (MOGA), an improved multi-objective GA with elites maintain is put forward based on non-dominated sorting genetic algorithm (NSGA). NSGA-II algorithm theory and parallel hybrid evolutionary theory is described in detail. The design principle, process and detailed implementations of...
A novel multi-objective evolutionary algorithm (MOEA) is developed based on Imperialist Competitive Algorithm (ICA), a newly introduced evolutionary algorithm (EA). Fast non-dominated sorting and the Sigma method are employed for ranking the solutions. The algorithm is tested on six well-known test functions each of them incorporate a particular feature that may cause difficulty to MOEAs. The n...
s: In this paper, we define the portfolio return as fuzzy average yield and risk as hybrid-entropy and variance to deal with the portfolio selection problem with both random uncertainty and fuzzy uncertainty, and propose a mean-variance hybrid-entropy model (MVHEM). A multi-objective genetic algorithm named Non-dominated Sorting Genetic Algorithm II (NSGA-II) is introduced to solve the model. W...
under an intensive competitive environment, the construction industry is facing pressure to meet the higher customer expectations under a tighter budget. on the other hand, construction is one of the main sectors generating greenhouse gases. according to published statistics, construction industry is one of the most important resources of greenhouse emissions in the world. therefore, based on t...
Analysis of population structure and organization with DNA-based markers can provide important information regarding the history and evolution of a species. Linkage disequilibrium (LD) analysis based on allelic associations between different loci is emerging as a viable tool to unravel the genetic basis of population differentiation. In this article, we derive the EM algorithm to obtain the max...
We consider the context of partial sorting. We address the problem of finding the parameters of the FlowSort method using an existing categorization. This contribution constitutes an extension of a method we have developed in the context of complete sorting. It relies on the use of a dedicated Genetic Algorithm based on variations of search parameters. We show how to manage the problem of corre...
In this article, the multi-objective optimization of cylindrical aluminum tubes under axial impact load is presented.The absorbed energy and the specific absorbed energy (SEA) are considered as objective functions while the maximum crush load should not exceed allowable limit. The geometric dimensions of tubes including diameter, length and thickness are chosen as design variables. The Non-domi...
With the huge global and wide range of attention placed upon quality, promoting and optimize the reliability of the products during the design process has turned out to be a high priority. In this study, the researcher have adopted one of the existing models in the reliability science and propose a bi-objective model for redundancy allocation in the series-parallel systems in accordance with th...
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