Title :
Comparing inertia weights and constriction factors in particle swarm optimization
Author :
Eberhart, R.C. ; Shi, Y.
Author_Institution :
Purdue Sch. of Eng. & Technol., Indianapolis, IN, USA
Abstract :
The performance of particle swarm optimization using an inertia weight is compared with performance using a constriction factor. Five benchmark functions are used for the comparison. It is concluded that the best approach is to use the constriction factor while limiting the maximum velocity Vmax to the dynamic range of the variable Xmax on each dimension. This approach provides performance on the benchmark functions superior to any other published results known by the authors
Keywords :
evolutionary computation; benchmark functions; constriction factors; inertia weights; particle swarm optimization; Acceleration; Computational modeling; Dynamic range; Evolutionary computation; Genetic algorithms; Nonlinear equations; Particle swarm optimization; Random number generation;
Conference_Titel :
Evolutionary Computation, 2000. Proceedings of the 2000 Congress on
Conference_Location :
La Jolla, CA
Print_ISBN :
0-7803-6375-2
DOI :
10.1109/CEC.2000.870279
