This paper presents an improved particle swarm optimization algorithm (EWPSO) with a novel strategy for inertia weight. In the new algorithm, nonlinear inertia weight is proposed. The new weight is an exponential function of the minimal and maximal fitness of the particles in each iteration. The set of benchmark function was used to test the new method. The results were compared with those obtained through the standard PSO with linear decreasing inertia weight (LDW-PSO) and RNW-PSO. Simulation results showed that EWPSO is more effective for the tested problems than both LDW-PSO and RNW-PSO.


Optimization Particle swarm optimization Inertia weight 


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Institute of Information Technology, Lodz University of TechnologyŁodźPoland

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