Title :
Pareto optimality and particle swarm optimization
Author :
Baumgartner, U. ; Magele, Ch ; Renhart, W.
Author_Institution :
Inst. for Fundamentals & Theor. in Electr. Eng., Graz Univ. of Technol., Austria
fDate :
3/1/2004 12:00:00 AM
Abstract :
Real-world optimization problems often require the minimization/maximization of more than one objective, which, in general, conflict with each other. These problems (multiobjective optimization problems, vector optimization problems) are usually treated by using weighted sums or other decision-making schemes. An alternative way is to look for the pareto-optimal front. In this paper, the particle swarm algorithm is modified to detect the pareto-optimal front.
Keywords :
decision making; optimisation; stochastic processes; Pareto optimality; Pareto-optimal front; decision-making schemes; maximization; minimization; multiobjective optimization; particle swarm optimization; real-world optimization; stochastic optimization; vector optimization problems; weighted sums; Birds; Decision making; Optimization methods; Particle swarm optimization; Partitioning algorithms; Poles and towers; Sampling methods; Space technology; Stochastic processes; Transmission line theory;
Journal_Title :
Magnetics, IEEE Transactions on
DOI :
10.1109/TMAG.2004.825430