Paper Info
Title
Particle swarm optimization and fitness sharing to solve multi-objective optimization problems
Abstract
The particle swarm optimization algorithm has been shown to be a competitive heuristic to solve multi-objective optimization problems. Also, fitness sharing concepts have shown to be significant when used by multi-objective optimization methods. In this pa- per we introduce an algorithm that makes use of these two main concepts, particle swarm optimization and fit- ness sharing to tackle multi-objective optimization prob- lems.
Year
DOI
Venue
2005
10.1109/CEC.2005.1554827
Evolutionary Computation, 2005. The 2005 IEEE Congress
Keywords
Field
DocType
heuristic programming,nonlinear programming,particle swarm optimisation,competitive heuristic,fitness sharing,multiobjective optimization problems,particle swarm optimization
Continuous optimization,Mathematical optimization,Derivative-free optimization,Computer science,Meta-optimization,Multi-objective optimization,Multi-swarm optimization,Fitness approximation,Artificial intelligence,Imperialist competitive algorithm,Machine learning,Metaheuristic
Conference
Volume
ISBN
Citations 
2
0-7803-9363-5
23
PageRank 
References 
Authors
1.66
9
2
Name
Order
Citations
PageRank
Salazar-Lechuga, M.1231.66
Jonathan E. Rowe245856.35