2. About ACO in Comm.. ObjectiveResearch Info.AbstractAnt Colony OptimizationSummaryAppendix. 3. Objective. To study current Ant Colony Optimization algorithms and existing routing protocols. This is to identify the various types of problems in communications networks design (especially routing
1. 1 Ant Colony Optimization Approach to Communications Networks Design Monday, July 30, 2012
Bau Yoon Teck [email protected]
MMU FIT COE for CAIIC
2. 2 About ACO in Comm. Objective
Ant Colony Optimization
3. 3 Objective To study current Ant Colony Optimization algorithms and existing routing protocols. This is to identify the various types of problems in communications networks design (especially routing) that Ant Colony Optimization (ACO) can tackle.
To apply ACO algorithms for the construction of degree-constrained communications networks.
To perform routing in degree-constrained communications network using ACO and its hybrid versions.
To compare the performance of conventional as well as existing ACO routing techniques against that of the proposed algorithms.
4. 4 Research Info. Type of Research: Applied /Fundamental
Beneficiaries of Project: Researchers and companies
involved in communications networks design
Product/Services: Software Tools
Researchers: Mr. Bau Yoon Teck
Source of Funding: nil
Status of Project: Ongoing
5. 5 Abstract Ant Colony Optimization (ACO) is an algorithm for discrete optimization
and multiagent meta-heuristic approach to difficult NP-hard combinatorial
optimization problems and routing in communications networks. The
inspiring source of ACO is the pheromone trail laying and following
behaviour of real ants, which use pheromones as a communication
medium. We apply ACO algorithms to routing problems in
communications networks under static and dynamic conditions. This
study is divided into three parts. The first part aims to identify various
existing routing protocols and compare their performance to that of the
ACO. The second part of this research involves formulating and applying
the ACO algorithms to construct degree-constrained communications
networks. The ACO routing will then be applied on the constructed
networks, taking into consideration different traffic conditions. The final
part of the study will focus on designing hybrid ACO routing protocols
that incorporates genetic algorithms (GAs) and reinforcement learning.
6. 6 Ant Colony Optimization