International Workshop on Emergent Synthesis -IWES '99 December 6-7, 1999, Kobe DIVIDED RANGE GENETIC ALGORITHMS IN MULTIOBJECTIVE OPTIMIZATION PROBLEMS
نویسندگان
چکیده
In this paper, Divided Range Genetic Algorithm in Multi objective optimization Problems (DRGA) is proposed. In this method, population of GAs is sorted with respect to the objective function and divided into sub populations. In this model, the Pareto optimum solutions which are close to each other are collected by one sub population. Therefore, by this algorithm, the calculation e ciency is increased, and the neighborhood search can be performed. Through the numerical examples, the followings are made cleared . DRGA is very suitable GA model for parallel processing. DRGA can derive the good solutions compared to the single population model and the distributed model.
منابع مشابه
Divided Range Genetic Algorithms in Multiobjective Optimization Problems
In this paper, Divided Range Genetic Algorithm in Multi objective optimization Problems (DRGA) is proposed. In this method, population of GAs is sorted with respect to the objective function and divided into sub populations. In this model, the Pareto optimum solutions which are close to each other are collected by one sub population. Therefore, by this algorithm, the calculation efficiency is i...
متن کاملMultiobjective Imperialist Competitive Evolutionary Algorithm for Solving Nonlinear Constrained Programming Problems
Nonlinear constrained programing problem (NCPP) has been arisen in diverse range of sciences such as portfolio, economic management etc.. In this paper, a multiobjective imperialist competitive evolutionary algorithm for solving NCPP is proposed. Firstly, we transform the NCPP into a biobjective optimization problem. Secondly, in order to improve the diversity of evolution country swarm, and he...
متن کاملApproaches Based on Genetic Algorithms for Multiobjective Optimization Problems
In engineering, it is often necessary to formulate problems in which there are several criteria or objectives. It is unlikely that a solution that optimizes one of the objectives will be optimal for any of the others. Compromise solutions are therefore sought such that no other solutions are better in any one objective while remaining no worse in the others. These types of problems are known as...
متن کاملSatellite Conceptual Design Multi-Objective Optimization Using Co Framework
This paper focuses upon the development of an efficient method for conceptual design optimization of a satellite. There are many option for a satellite subsystems that could be choice, as acceptable solution to implement of a space system mission. Every option should be assessment based on the different criteria such as cost, mass, reliability and technology contraint (complexity). In this rese...
متن کاملOptimization of e-Learning Model Using Fuzzy Genetic Algorithm
E-learning model is examined of three major dimensions. And each dimension has a range of indicators that is effective in optimization and modeling, in many optimization problems in the modeling, target function or constraints may change over time that as a result optimization of these problems can also be changed. If any of these undetermined events be considered in the optimization process, t...
متن کامل