Pareto Genetic Algorithm Based on IFI and FUA
Guanci Yang · Jisuanji gongcheng · 2007
This paper proposes a fast Pareto genetic algorithm for searching pareto optimal solution set.It is based on a new approach for fast evaluation of fitness of individuals and a clustering based external population update scheme for maintaining population diversity and even distribution of Pareto solutions.Experiments on a set of multi-objective knapsack optimization problems shows that FPGA can obtain high-quality,well distributed non-dominated Pareto solutions with less computational efforts compared to other state-of art algorithms,it has advantages in its convergence speed and quality over the state-of-the-art SPEA algorithm.