Title :
Optimization and Simulation of a MO Problem Solved by GAs and PSO
Author :
Lei, Xiujuan ; Shi, Zhongke ; Wang, Laijun
Author_Institution :
Shaanxi Normal Univ., Xian
Abstract :
This paper solves an economic multi-objective optimization problem through two improved intelligent optimization methods, one is multi-objective genetic algorithms named RNPGA (random niche pareto genetic algorithms), and the other is improved PSO (particle swarm optimization) with linear inertia weight reduction, which the constraints is in a specified region. Moreover we calculate the model through programming and give the simulation results. Computing results show the validity and advancing of the methods and the PSO algorithm is more quickly to solve the actual problem.
Keywords :
Pareto optimisation; genetic algorithms; particle swarm optimisation; economic multiobjective optimization problem; intelligent optimization methods; linear inertia weight reduction; multiobjective genetic algorithms; particle swarm optimization; random niche Pareto genetic algorithms; Arithmetic; Computational modeling; Constraint optimization; Educational institutions; Environmental economics; Genetic algorithms; Optimization methods; Pareto optimization; Particle swarm optimization; Space technology; Algorithms; Genetic; Multi-objective Optimization; Particle Swarm Optimization;
Conference_Titel :
Natural Computation, 2007. ICNC 2007. Third International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2875-5
DOI :
10.1109/ICNC.2007.522
