A multi-objective natural aggregation algorithm for optimizing user allocation matrix in visible light communication

Abstract

Allocating users to LED panels in a visible light communication (VLC) environment is a non-convex multi-objective constrained optimization problem. The computational complexity and accuracy of the optimization are the key factors to deal with in a VLC environment. In this manuscript, initially the user allocation problem is formulated as a single objective optimization problem by using sum-utility function of data rate and blockage probability. Then these two contradictory objective functions are simultaneously optimized by a new multi-objective natural aggregation algorithm (MONAA). This proposed algorithm is inspired by the aggregation behavior of cockroaches which help them to determine the darkest spot in a search space. The performance of this multi-objective algorithm is compared with NSGA-II, MOPSO, MOEA/D and MOSOS on eight unconstrained and six constrained mathematical function optimizations. In single objective and multi-objective cases, superior performance is demonstrated by the natural aggregation algorithm for solving the user allocation matrix optimization.