Search

In the analysis of basic optimization method of multi-objective GA, papers was proposed on the improved GA of weights that was based on an improved elitist preservation strategy. Firstly, The algorithm combined improved strategy of the (μ + λ) evolution with GA that is based on weights coefficients. Secondly, it continuously detected the population size and restarted some groups. So they could ensure the diversity of both the population and the search direction, thus ensuring the search results of the Pareto values. Simulation results had demonstrated that the improved GA and MPP model had the effectiveness and feasibility in network planning cost and schedule optimization. In order to address the existence problems that improved algorithm was running slow, we had combined the Niched-Pareto with improved algorithm. Then the result was presenting a hybrid algorithm. The simulation showed that this hybrid algorithm had certain advantages in the search effectiveness and efficiency.