With the rapid development of communication
networks, the quality of service (QoS) on such networks has
become an important research topic. With regard to ad hoc
networks, this paper presents an evolutionary algorithm (EA)
and an ant colony algorithm (ACA) to serve as the basis
for a QoS multicast routing algorithm (EA-ACA-QMRA).
This algorithm combines the rapid global search capability
and robustness of EAs with the pheromone feedback factors
of ACAs while accounting for multiple constraints, includ-
ing constraints related to delay, delay jitter, packet delivery
ratio, bandwidth and cost. For the case of self-adapting ad
hoc networks in particular, our new algorithm is far supe-
rior to traditional ACAs. Our experimental results show that
the EA-ACA-QMRA can address multiple constraints in the
QoS multicast routing problem and can achieve higher accu-
racy and faster convergence than can traditional ACAs in
terms of the end-to-end delay and packet delivery ratio. The
proposed algorithm provides an effective means of solving
the QoS multicast routing problem for ad hoc networks, and it is better than the traditional methods at avoiding network
congestion.

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