Quantum heuristics can significantly expand the list of applications for which quantum computers have a significant advantage in the same trend of researches that has crossed the classical operational research community from decades in numerous areas, including but not limited to scheduling and routing. Lately Farhi et al [1] in 2002 introduced a promising Quantum Approximate Optimization Algorithm which formally defines a quantum alternating operator ansatz (QAOA) supporting a large and potentially useful set of states which create an alternative to the Adiabatic Optimization. In this paper we investigate Adiabatic Optimization for resolution of two classical optimizaton problems.