Inertia Control to Escape Local Minima of Non-Linear Functions in Particle Swarm Optimization

• Tiago Silveira UNIFAL
• Humberto César Brandão de Oliveira UNIFAL
• Luiz Eduardo da Silva UNIFAL

Abstract

This work presents a mechanism to reduce the chances of the optimization process of nonlinear functions stagnating in local minima, using the meta-heuristic Particle Swarm Optimization. This mechanism is a non-monotonic way to control the particle inertia, which is one of the factors responsible for movement during the optimization process. The experimental results were compared to the PSO original model aiming to show the potential to find a better solution in the benchmark functions for complex problems.

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