Abstract
Wireless Sensor Network Deployment (WSND) is one multi-objective optimization problem that has been tackled adequately in the literature. However, one specific aspect was not fully covered which is the effect of one of its decision variables on the number of dimensions in the solution space. Typically, researchers solve it by considering fixed value of the mentioned decision variable or they avoid it in the explicit representation. This study focuses on the dimension selector of the problem of WSND and it proposes building a dimension profiler for selecting the best dimension to operate multi-objective optimization. The work is evaluated based on two famous multi-objective optimization algorithms, namely, multi-objective particle swarm optimization (MOPSO) and non-dominated sorting genetic algorithms (NSGA-II). The work shows the effect of the dimensionality changing with respect to the number of non-dominated solutions by showing peaks at certain dimensions.
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