Multi-objective ACO algorithm for WSN layout: performance according to number of ants

Wireless sensor networks monitor physical or environmental conditions. One of the key objectives during their deployment is full coverage of the monitoring region with a minimal number of sensors and minimised energy consumption of the network. This problem is hard, from the computational point of view. Thus, the most appropriate approach to solve it is application of some metaheuristics. In this paper we apply multi-objective ant colony optimisation to solve this important telecommunication problem. The number of the agents (ants) is one of the important algorithm parameters in the ant colony optimisation metaheuristics. The needed computational resources for algorithm performance depends on number of ants. When the number of ants increases the computational time and used memory increase proportionally. Thus it is important to find the optimal number of agents needed to achieve good solutions with minimal computational resources. Therefore, the aim of the presented work is to study the influence of the number of ants on the algorithm performance.