An Artificial Bee Colony Algorithm for Optimizing the Design of Sensor Networks

Abstract

The sensor network design problem (SNDP) consists of theselection of the type, number and location of the sensors to measure aset of variables, optimizing a specified criteria, and simultaneously satisfying the information requirements. This problem is multimodal andinvolves several binary variables, therefore it is a complex combinatorialoptimization problem. This paper presents a new Artificial Bee Colony(ABC) algorithm designed to solve high scale designs of sensor networks.For this purpose, the proposed ABC algorithm has been designed tooptimize binary structured problems and also to handle constraints tofulfil information requirements. The classical version of the ABC algorithm was proposed for solving unconstrained and continuous optimization problems. Several extensions have been proposed that allow theclassical ABC algorithm to work on constrained or on binary optimization problems. Therefore the proposed approach is a new version of theABC algorithm that combines the binary and constrained optimizationextensions to solve the SNDP. Finally the new algorithm is tested usingdifferent systems of incremental size to evaluate its quality, robustness, and scalability.