Quality of service routing strategy using supervised genetic algorithm
Zhaoxia Wang, Yugeng Sun, Zhiyong Wang, Huayu Shen · Singapore Management University Institutional Knowledge (InK) (Singapore Management University) · 2007
A supervised genetic algorithm (SGA) is proposed to solve the quality of service (QoS) routing problems in computer networks. The supervised rules of intelligent concept are introduced into genetic algorithms (GAs) to solve the constraint optimization problem. One of the main characteristics of SGA is its searching space can be limited in feasible regions rather than infeasible regions. The superiority of SGA to other GAs lies in that some supervised search rules in which the information comes from the problems are incorporated into SGA. The simulation results show that SGA improves the ability of searching an optimum solution and accelerates the convergent process up to 20 times.