The Solving of Multi-Objective Network Designing Problem Based on Genetic Algorithm

The genetic algorithm is used to solve the multi-objective networks design problem that requires selecting a best route to make a balance with cost and delay of the route. Firstly, the mathematical model of the problem is given, then the nondominated sorting generate algorithm is used to solve the model. The algorithm uses coding method with integer to form chromosomes and an initial population is generated randomly that satisfies all constraints. In selecting process, two objective-value delay and cost are calculated, the chromosomes are ranked according to the objective value, then the better chromosomes is selected for the crossover processing by the roulette method. The single point crossover based on deleting the cricoidpsilas genes is used in crossover process. Several examples of network design are given and the computing result shows that the approximate global optimal solution of the problem can be quickly obtained, and the solutions are obtained with high accuracy.