MQHOA algorithm with energy level stabilizing process

Abstract

An improved multi-scale quantum harmonic oscillator algorithm (MQHOA) with energy level stabilizing process was proposed analogizing to quantum harmonic oscillator's wave function. Inspired by quantum model, the op-timization problem was transformed to finding ground state wave function of bound state. Harmonic oscillator potential well was used to approach objective function under the condition of Taylor approximation. Energy level stabilization, en-ergy level reduction, scale reduction were the basic iterative convergence processes of MQHOA, coinciding with its physical model. Only one subjective control parameter was needed in MQHOA whose wave function and zero-point en-ergy were defined with reference to quantum model. Experimental results show that MQHOA's performance is superior to several other common optimization algorithms. For high dimensional testing functions including Ackley、Griewank、Sphere、Sum Squares、Zakharov, etc, the global optimums can be obtained precisely with 100% probability.

Keywords

• optimization algorithm
• function optimization
• MQHOA
• wave function
• ground state