hBOATM (the hierarchical
Bayesian Optimization Algorithm) is an advanced
scalable optimization procedure that quickly solves problems
of bounded and hierarchical difficulty, often in subquadratic time.
The hBOATM solution
technique can be used to solve a broad and critical class of problems
(the class Nobel Laureate Herbert Simon called nearly decomposable problems)
and because of its power and speed, hBOATM
will provide its licensees with a qualitative
and quantitative competitive advantage over their unlicensed
competitors.
Developed
by the University of Illinois' Illinois Genetic Algorithms Laboratory
(IllIGAL) by Dr. Martin Pelikan and renowned genetic algorithm expert
Professor David E. Goldberg, hBOATM can
now be licensed by companies and organizations
that need to solve difficult problems quickly, reliably, and accurately.