PSO with Gompertz increasing inertia weight

This paper implements Standard Particle Swarm Optimization (PSO) and a new algorithm that aims to be better than the classical PSO. An m-file code is used to simulate the Standard Particle Swarm Optimization and it is evaluated using the five well known benchmark functions namely Sphere, Ackley, Rastrigin, Rosenbrock, and Shcwefel's Problem 2.26. A new PSO algorithm known as Gompertz increasing inertia weight (GIIW) is proposed and also implemented as above. The comparison has been simulated with standard PSO. From experiments, it shows that PSO with GIIW gives good performance with quick convergence capability and aggressive movement narrowing towards the solution region.

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