A new method for multi-objective optimization problem based on multi-ant-colony algorithm
In order to improve the solving performance of multi-objective optimization problem, a new method based on multi-ant-colony algorithms is proposed. Aiming to enhance the diversity of pareto solutions, quasi-pareto solutions are constructed by sub-ant-colony algorithm which adopts its own and other sub-ant-colony heuristic information and quasi-pareto solutions obtained by every ant are used for control judgment. The constructed farther-group ants with the quasi-pareto solutions which act as space nodes constitute TSP(Traveling Salesman Problem), and then the solutions of the TSP act as the front of solutions for multi-objective optimization problem, hence lead to the enhancement of the uniform distribution of pareto solutions. Experiment results show that the obtained pareto solutions by multi-ant-colony optimization based on multi-classification methods have many advantages, such as the diversity and uniform distribution of solutions.
multi-ant-colony algorithm multi-objective optimization function optimization optimization method
Daohua Liu Gongping Chen
School of Computer and Information Technology Xinyang Normal university Xinyang, China Network Information Center Xinyang Normal university Xinyang, China
国际会议
太原
英文
605-609
2010-10-22（万方平台首次上网日期，不代表论文的发表时间）