Scheduling Functions for Position Updating in Population Based Optimization Algorithms

Population based optimization algorithms are algorithms in which a set of input values (or candidate solutions, or positions within the problem search space) is maintained through the course of the algorithm, as opposed to non-population-based methods which generally examine only one input value at each iteration of the algorithm. We shall refer to these input values as “individuals”, although common terminology varies based on the context of and (often biological) inspiration for specific algorithms. In general terms, a typical procedure for a population-based single-objective optimization algorithm is as follows: