  To more flexibly balance between exploration and exploitation, a new
meta-heuristic method based on Uncertainty Principle concepts is proposed in
this paper. UP is is proved effective in multiple branches of science. In the
branch of quantum mechanics, canonically conjugate observables such as position
and momentum cannot both be distinctly determined in any quantum state. In the
same manner, the branch of Spectral filtering design implies that a nonzero
function and its Fourier transform cannot both be sharply localized. After
delving into such concepts on Uncertainty Principle and their variations in
quantum physics, Fourier analysis, and wavelet design, the proposed framework
is described in terms of algorithm and flowchart. Our proposed optimizer's idea
is based on an inherent uncertainty in performing local search versus global
solution search. A set of compatible metrics for each part of the framework is
proposed to derive preferred form of algorithm. Evaluations and comparisons at
the end of paper show competency and distinct capability of the algorithm over
some of the well-known and recently proposed metaheuristics.
