Dynamic scale quantum‐inspired optimisation algorithm under harmonic oscillator potential well

A quantum‐inspired optimisation algorithm with dynamic scale sampling is proposed for converging to the ground state efficiently to obtain the optimal solution. The proposed algorithm maintains diversity to discourage premature convergence through the niching method. Dynamic adjustment of sampling resolution is utilised to find a balance between exploration and exploitation. Energy level transition inside each niche and niches energy balance among niches improve the searching efficiency by guidance energy information of energy equilibrium point. The experimental results on benchmark function sets with compared algorithms show that the proposed scheme is dominant in accuracy and stability.