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Wireless mesh networks (WMN) are believed to be a highly promising technology and will play an increasingly important role in future generation wireless mobile networks. Routing in WMN is a challenging problem as a result of highly dynamic topology as well as bandwidth and energy constraints. The swarm intelligence paradigm, such as ant colony optimization (ACO), has recently been demonstrated as an active approach for routing in both wired and wireless networks. We designed a novel ACO-based multicasting routing algorithm. In the proposed algorithm, a source-based approach is adapted to build a multicast tree among all the multicast members, and an evolutional scheme for the original multicast tree is designed to find a more optimal multicast tree. In addition the evolutional scheme also acts as a local recovery technique when some intermediate nodes move away. Compared with ODMRP and MAODV, the proposed algorithm performs better in terms of average delay, success ratio and efficiency.