tailieunhanh - Genetic algorithms varying size of population and multi - objective optimization problems, apply to solve animal feed optimization problem

Population size is an important parameter in Genetic Algorithms (GAs). How population size is reasonable is a matter of concern when designing programs using GAs. Overall, population size is defined as a given parameters and unchanged in evolution processes. This paper presents research results that GAs population size changes affecting the diversity of populations and apply to multiobjective optimization problems, specific the animal feed optimization problem. | Nguyễn Thu Huyền và Đtg Tạp chí KHOA HỌC & CÔNG NGHỆ 93(05): 75 - 79 GENETIC ALGORITHMS VARYING SIZE OF POPULATION AND MULTI -OBJECTIVE OPTIMIZATION PROBLEMS, APPLY TO SOLVE ANIMAL FEED OPTIMIZATION PROBLEM Nguyễn Thu Huyền1, Lương Sỹ Ước2, Vũ Mạnh Xuân3* 2 1 College of Information and Communication Technology - TNU College of Technology and Economics – TNU, 3College of Education - TNU ABSTRACT Population size is an important parameter in Genetic Algorithms (GAs). How population size is reasonable is a matter of concern when designing programs using GAs. Overall, population size is defined as a given parameters and unchanged in evolution processes. This paper presents research results that GAs population size changes affecting the diversity of populations and apply to multiobjective optimization problems, specific the animal feed optimization problem. Keywords: genetic algorithms, population size, diversity of populations, animal feed optimization problem. INTRODUCTION* In GAs, population size is an important parameter and is determined after establishing the program. Population size is how much is appropriate, it depends on the problem that we solve. Typically, population size is fixed mean number of individuals in the population is unchanged from generation to generation. But in nature, population size is not fixed, so the study of GA is applied to the course. First, it is necessary to determine the initial population size, this number can change over generations. But changed will be what? when we increase the size? when we will increase only?. are the problems to be solved. This paper studies and proposes an algorithm that GAs population size is not fixed. Test results are presented in multi-objective optimization problems, special the animal feed optimization problem. The paper is structured as follows: After the preamble is proposed GAs with population size adjustment. The next section presents briefly the problem multi-objective optimization problem .