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One of the main design aspects of Wireless Sensor Networks (WSNs) is the deployment strategy of the sensors. In general, WSN deployment methods fall under two categories: planned deployment and random deployment. In this paper, we focus on planned deployment which is defined as selectively deciding the locations of the sensors to optimize one or more design objectives of the WSN under some given constraints. There have been a large number of studies which proposed algorithms for solving the planned deployment problem. In this paper, we present a novel classification of the algorithms proposed in the literature for planned deployment of WSNs, based on the mathematical approach used for modeling and solving the deployment problem. Four distinct mathematical approaches are presented: Genetic Algorithms, Computational Geometry, Artificial Potential Fields and Particle Swarm Optimization. For each approach, we provide a discussion of its background and basic mathematical foundation. We then review the algorithms which belong to each approach and provide a comparison between them in terms of their objectives, assumptions and performance. Based on our extensive survey, we discuss the strengths and limitations of the four approaches and compare them in terms of the different WSN design factors.