A novel multi-level quantization scheme for discrete particle swarm optimization
Hwachang Song, Ryan Diolata, Young Hoon Joo · 2009
This paper presents a novel multi-level quantization scheme which best approximates the sigmoid function for multi-value discrete variable transformation in PSO. We define the set of multi-level quantization as integer multiples of powers-of-two terms to efficiently approximate the sigmoid function in transforming particle's position into multilevel discrete values. In this paper, the feasibility of the proposed technique was tested in photovoltaic (PV) system allocation problem, and a comparison study with genetic algorithm (GA) is performed to show the quality of the solutions obtained.