Optimal stopping time of compact genetic algorithm on deceptive problem using real options analysis

This paper proposes using a decision contour derived from real options analysis, which is an evaluation tool for investment under uncertainty, to suggest an optimal stopping time of the compact genetic algorithm on the trap problem. The proposed criterion provides a stopping boundary, where termination is optimal on one side and continuation is on the other. A generic stopping function is formulated with an exercise region that scales well. The new stopping policy helps save on computational effort, and the evolutionary process reaches a higher solution quality when the reset method is incorporated. The proposed technique can be applied to analyze other problems.