A Hybrid Ant Colony Optimization Algorithm for Topology Optimization of Local Area Networks

Ant colony optimization (ACO) is a well-known optimization technique and has been extensively used to a solve a variety of computationally hard problems. One such hard problem is found in the domain of local area network (LAN) topological optimization. The problem, due to its various design objectives and technical constraints, is considered a complex optimization problem. Due to this complexity, use of an intelligent design algorithm is inevitable in order to obtain a quality solution in a reasonable time. This paper proposes a new intelligent optimization algorithm that integrates features of the ACO algorithm and the simulated evolution (SE) algorithm. The performance of the proposed hybrid algorithm, termed as ACOSE, is empirically evaluated and compared with the ACO and SE algorithms. Preliminary results indicate that ACOSE is able to produce better results on the LAN design problem considered herein in terms of quality of solution compared to either ACO or SE.