Abstract
Biologically inspired ant colony optimisation (ACO) has been used in several applications to solve NP-hard combinatorial optimisation problems. An interesting area of application for ACO-based algorithms is their use in wireless sensor networks (WSNs). Due to their robustness and self-organisation, ACO-based algorithms are well-suited for the distributed, autonomous and self-organising structure of WSNs. While the original ACO-based algorithm and its direct descendants can take only one objective into account, multi-objective ant colony optimisation (MOACO) is capable of considering multiple (conflicting) objectives simultaneously. In this chapter, a detailed review and summary of MOACO-based algorithms and their applications in WSNs is given. In particular, a taxonomy of MOACO-based algorithms is presented and their suitability for multi-objective combinatorial optimisation problems in WSNs is highlighted.
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