Virus Optimization Algorithm for Curve Fitting Problems
In this paper, a newly developed metaheuristic for continuous optimization problems, named Virus Optimization Algorithm (VOA) which imitates the behavior of the virusis proposed to solve the curve fitting problems. This metaheuristic can be considered as a type of evolutionary algorithms (EA) with reproduction and cell maintenance mechanisms incorporated. VOA is a population-based method that begins the search with a small set of viruses and the number of those viruses will grow at each replication (iteration). The host cell represents the entire search space while the virus reproduction denotes the generation of new solutions. In addition, a mechanism called antivirus is in charge of protecting the cell against the viruses. The whole process continues iteratively until the stopping criterion is reached. The curve fitting problems to be solved is the generalized Gaussian mixture model for two stock index markets. Several algorithms such as Particle Swarm Optimization, Genetic Algorithm, and Harmony Search are used to compare with the proposed VOA. As a conclusion from the tests performed, the proposed VOA shows to be a competitive tool for solving this type of continuous optimization problems.
virus optimization algorithm metaheuristics curve fitting market indices
Yun-Chia Liang Josue R. Cuevas
Department of Industrial Engineering and Management,Yuan Ze University, Taiwan, China
国际会议
The Institute Industrial Engineera Asian Conference 2011(2011年国际工业工程师协会亚洲会议)
上海
英文
163-175
2011-06-10（万方平台首次上网日期，不代表论文的发表时间）