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The complex nature of wireless local area networks (WLAN) design has led many of the deployments being done in an ad-hoc fashion without efficient design methodologies. Although this approach may work for a small environment with a small number of access points, it is infeasible to use such a process when designing a larger wireless infrastructure. Due to the low cost that is indicative of WLAN deployments, many practitioners view formal optimization techniques as being too complex and costly to implement. There have been a number of research works that investigate the use of formal optimization techniques for the accurate design of a WLAN. Unfortunately, the approaches taken do not address one major issue when designing a complex and demanding wireless network infrastructure, namely scalability. An optimization algorithm must consider a multitude of design criteria and therefore needs to be scalable to be successfully applied to large scenarios. The main contribution of the work presented in this paper is the development of a scalable optimization algorithm based on the tools of distributed artificial intelligence, which overcomes the failings of current approaches and can be utilized for WLAN design regardless of size or complexity of site specific requirements.