The fair bandwidth allocation is an important issue in the multicast network to serve each multicast traffic at a fair rate commensurate with the receiver’s capabilities and the capacity of the path of the traffic. The lexicographically fair bandwidth allocation problem is considered and formulated as a nonlinear integer programming problem. A nonincreasing convex function of the bandwidth of the virtual sessions is employed to maximize the bandwidth of each virtual session from the smallest.
To solve the fairness problem a genetic algorithm (GA) based on the fitness function, ranking selection and the shift crossover and a tabu search based on the intensification and diversification are developed. Outstanding performance is obtained by the proposed Tabu Search in various multicast networks. The effectiveness of the Tabu Search becomes more powerful as the network size increases.