METHOD OF CONSTRAINED GLOBAL OPTIMIZATION

We present a new method for optimization: constrained global optimizat ion (CGO). CGO iteratively uses a Glauber spin flip probability and th e Metropolis algorithm. The spin flip probability allows changing only the values of variables contributing excessively to the function to b e minimized. We illustrate CGO with two problems-Thomson's problem of finding the minimum-energy configuration of unit charges on a spherica l surface, and a problem of assigning offices-for which CGO finds bett er minima than other methods. We think CGO will apply to a wide class of optimization problems.