A New Vector Particle Swarm Optimization for Constrained Optimization Problems
Chaoli Sun, Jianchao Zeng, Jeng‐Shyang Pan · 2009
A new vector particle swarm optimization (NVPSO) is proposed to solve constrained optimization problems in this paper. In NVPSO, we introduce a shrinkage coefficient to ensure that all dimensions of a particle are within lower and upper bounds, and a new function to determine whether the particle is within the feasible region. One-dimensional search optimization methods are selected in NVPSO algorithm to produce a new position which is guaranteed to be in the feasible region for the particle which escapes from the feasible region. The whole process is dealt as vector mode. The experimental results show that the principle of NVPSO this paper proposed is simple, relatively effective and efficient.