The algorithm introduced in this chapter is a growth algorithm. Growth algorithm is a feasible approach for combinatorial optimization problems, which can be solved step by step. After one step is taken, the original problem becomes a sub-problem. In this way, the problem can be solved recursively. For the growth algorithm, the difficulty lies in that for a sub-problem, there are several candidate choices for current step. Then, how to select the most promising one is the core of growth algorithm. By basic greedy algorithm, we use some concept to compute the fitness value of candidate choice, then, we select one with highest value. The value or fitness is described by quantified measure. The evaluation criterion can be local or global. In this chapter, a novel greedy