J Intell Manuf (2012) 23:2057–2067 DOI 10.1007/s10845-011-0507-7 A study on the performance of local search versus population-based methods for mesh router nodes placement problem Admir Barolli · Fatos Xhafa · Christian Sánchez · Makoto Takizawa Received: 4 October 2010 / Accepted: 24 January 2011 / Published online: 5 February 2011 © Springer Science+Business Media, LLC 2011 Abstract Node placement problems have been long inves- tigated in the optimization field due to numerous applications in facility location, logistics, services, etc. Such problems are attracting again the attention of researchers now from the net- working domain, and more especially from Wireless Mesh Networks (WMNs) field. Indeed, the placement of mesh rou- ters nodes appears to be crucial for the performance and operability of WMNs, in terms of network connectivity and stability. However, node placement problems are known for their hardness in solving them to optimality, and therefore heuristics methods are approached to near-optimally solve such problems. In this work we evaluate the performance of different heuristic methods in order to judge on their suitabil- ity of solving mesh router nodes problem. We have selected methods from two different families, namely, local search methods (Hill Climbing and Simulated Annealing) and pop- ulation-based methods (Genetic Algorithms). The former are known for their capability to exploit the solution space by constructing a path of visited solutions, while the later meth- ods use a population of individuals aiming to largely explore the solution space. In both cases, a bi-objective optimiza- A. Barolli · M. Takizawa Department of Computers and Information Science, Seikei University, 3-3-1 Kichijoji-Kitamachi, Musashino-Shi, Tokyo 1808633, Japan e-mail: admir.barolli@gmail.com M. Takizawa e-mail: makoto.takizawa@computer.org F. Xhafa (B ) · C. Sánchez Department of Languages and Informatics Systems, Technical University of Catalonia, C/Jordi Girona, 1-3, 08034 Barcelona, Spain e-mail: fatos@lsi.upc.edu C. Sánchez e-mail: csanchez@lsi.upc.edu tion consisting in the maximization of the size of the giant component in the mesh routers network (for measuring net- work connectivity) and that of user coverage are considered. In the experimental evaluation, we have used a benchmark of instances—varying from small to large size—generated using different distributions of mesh node clients (Uniform, Normal, Exponential and Weibull). Keywords Wireless mesh networks · Local search · Genetic algorithms · Size of giant component · User coverage Introduction Node placement problems have been long investigated in the optimization field due to numerous applications in location science (facility location, logistics, services, etc) and classi- fication (clustering). In such problems, we are given a num- ber of potential facilities to serve to costumers connected to facilities aiming to find locations such that the cost of serv- ing all customers is minimized. In traditional versions of the problem, facilities could be hospitals, polling centers, fire stations serving to a number of stationary clients and aim- ing to minimize some distance function in a metric space between stationary clients and such facilities. Recently, such problems are showing their usefulness to communication net- works, where facilities could be servers, routers, etc. offering connectivity services to clients. Facility location problems are showing their usefulness to communication networks, and more especially from Wire- less Mesh Networks (WMNs) field. Wireless Mesh Net- works (Akyildiz et al. 2005; Nandiraju et al. 2007) are currently attracting a lot of attention from wireless research and technology community due to their importance as a 123