Multi-Objective Optimization of Network Systems by Using ANT Algorithms

At the design stage, the availability of a network system can be improved by redundancy allocation or, for a fixed network topology, by selecting highly available elements as nodes and connection arcs. Yet these design choices are constrained by the available budget and other physical and logistic requirements. This paper formulates the network design problem as a multiple-objective optimization aiming at maximizing the network availability and minimizing its associated cost. The potential of using Ant algorithms to identify Pareto-optimal network designs with respect to the defined objectives is explored. For each solution, the network availability objectives is computed by a combination of Monte Carlo simulation and Cellular Automata. The Pareto-optimal solutions can be used by the decision-makers to identify compromise solutions which best satisfy their risk profiles. A sample network is solved as a demonstration of the proposed approach.