Genetic Algorithm (GA) is restricted by actual system computing ability. Because of the limited number of population and iteration, the choice of initiation Population is a vital of fact, which directly influents the result of algorithm and the efficiency. GA's Initiation Population is created by the path of well-proportioned choosing seed or stochastic choosing seed generally, but both of them have a vice of inefficient search. The paper, combining with interrelated theories in graph theory, brings forward two kinds of Optimization Algorithms of Initiation Population based on Minimize Spanning Tree Local-Effective-Information Theory towards the limitations of them, and we successes it to TSP by example analysis.