Hard deterministic particle swarm optimisation for certain result solution

Abstract

Stochastic optimisation's performance is globally acknowledged for its flexibility, robustness and performance - the result of optimisation is usually outstanding and acceptable. However, stochastic methods benefit from random variance to produce feasible results. However, there is one significant disadvantage when it comes to the certainty of results. The stochastic method may give an unsatisfied result. Even though it is an unlikely possibility, it can happen. Therefore, we propose an algorithm that eliminates this problem by changing the calculation core to a deterministic base. In this paper, we select Particle Swarm Optimisation (PSO) as the prototype algorithm and modify the particle moving method to generate an inevitable result. The results show that our process can produce a certain result solution, and the output from our deterministic algorithm is also acceptable, like the original algorithm.