In this paper, we present a new algorithm an Enhanced Annealing Genetic Algorithm for Multi-Objective Optimization problems (MOPs). The algorithm tackles the MOPs by a new quan titative measurement of the Pareto front coverage quality Coverage Quotient. We then correspondingly design an energy function, atness function and a hybridization framework, and manage to achieve both satisfactory results and guaranteed convergence.