Particle swarm inspired optimization algorithm without velocity equation

This paper introduces Particle Swarm Without Velocity equation optimization algorithm (PSWV) that significantly reduces the number of iterations required to reach good solutions for optimization problems. PSWV algorithm uses a set of particles as in particle swarm optimization algorithm but a different mechanism for finding the next position for each particle is used in order to reach a good solution in a minimum number of iterations. In PSWV algorithm, the new position of each particle is determined directly from the result of linear combination between its own best position and the swarm best position without using velocity equation. The results of PSWV algorithm and the results of different variations of particle swarm optimizer are experimentally compared. The performance of PSWV algorithm and the solution quality prove that PSWV is highly competitive and can be considered as a viable alternative to solve optimization problems.