Vector Evaluated Gravitational Search Algorithm (VEGSA) for multi-objective optimization problems
This paper presents a novel algorithm, which is based on Gravitational Search Algorithm (GSA), for multiobjective optimization problems. The proposed algorithm, which is called Vector Evaluated Gravitational Search Algorithm (VEGSA), uses a number of populations of particles. In particular, a popula...
| Main Authors: | , , , , , |
|---|---|
| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
IEEE
2012
|
| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/26988/ http://umpir.ump.edu.my/id/eprint/26988/1/Vector%20Evaluated%20Gravitational%20Search%20Algorithm%20%28VEGSA%29%20.pdf |
| Summary: | This paper presents a novel algorithm, which is based on Gravitational Search Algorithm (GSA), for multiobjective optimization problems. The proposed algorithm, which is called Vector Evaluated Gravitational Search Algorithm (VEGSA), uses a number of populations of particles. In particular, a population of particles corresponds to one objective function to be minimized or maximized. Simultaneous minimization or maximization of every objective function is realized by exchanging a variable between populations. Two versions of VEGSA algorithm are presented in this study. Convex and non-convex test functions on biobjective optimization problems are used to evaluate the effectiveness of the proposed VEGSA. |
|---|