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.

 

 



 

hBOATM technology is patent pending.
Copyright 2003