Abstract
Electric field intensity can be determined analytically, experimentally and numerically. Charge simulation method (CSM) is one of the most commonly used numerical methods for its many characteristics features. It can be used stand alone or in combination with other numerical methods. Sometimes optimisation techniques are used to facilitate the locating of the simulating charges as well as their values. Several optimisation techniques have emerged in the past decades that mimic biological evolution. The most representative techniques include genetic algorithms (GA) and particle swarm optimisation (PSO). Although PSO is more computationally efficient than GA, the later was used frequently to develop optimised versions of CSM during the last two decades. On the other hands, PSO technique was used recently only once to optimise the location of the simulating charges. In this study, the combination process between PSO and CSM became more convenient by optimising both charge locations and their values. This work eliminates the problems that were associated with the last trial and increases the degree of freedom that leads to solutions that are more realistic. The validity of the proposed method was verified by comparison with the analytical and numerical solutions.