Multicast Routing Problem with QoS Constraints is an NP-Complete Problem

The multicast routing problem with Quality of Service (QoS) constraints presents significant computational complexity, making it challenging to develop efficient solutions. This necessitates the application of robust optimization algorithms. The genetic simulated annealing algorithm represents a fusion of genetic algorithms and simulated annealing techniques, offering an enhanced approach for addressing such problems. This hybrid algorithm employs evolutionary mechanisms (selection, crossover, mutation) combined with temperature-dependent acceptance criteria to explore optimal solutions. Through simulated evolution and controlled temperature reduction, the algorithm effectively balances global exploration and local refinement. Implementing this approach typically involves designing chromosome structures representing routing paths, defining fitness functions that incorporate QoS metrics (bandwidth, delay, jitter), and establishing cooling schedules for convergence control. Consequently, applying genetic simulated annealing algorithms to solve QoS-constrained multicast routing problems constitutes a promising research direction with practical implementation potential.