A new global optimization algorithm for mixed-integer-discrete-continuous variables based on particles swarm optimization

摘要

This paper presents a new global optimization algorithm for mixed-integer-discrete-continuous variables. In the algorithm, an augmented objective function is constructed by introducing a penalty function to treat both the integer and discrete variables as continuous ones. Particles swarm optimization (PSO) is, then, applied to the augmented objective function to find a global optimal point.