Download Now Free registration required
This paper proposes and evaluates an evolutionary multi objective optimization algorithm, called EVOLT, which heuristically optimizes QoS (quality of service) parameters in communication networks. EVOLT uses a population of individuals, each of which represents a set of QoS parameters, and evolves the individuals via genetic operators such as crossover, mutation and selection for satisfying given QoS requirements. For evaluating EVOLT in real-world settings that have high-dimensional parameter and optimization objective spaces, this paper focuses on QoS optimization in safety-critical communication networks for electric power utilities. Simulation results show that EVOLT outperforms a well-known existing evolutionary algorithm for multi objective optimization and efficiently obtains quality QoS parameters with acceptable computational costs.
- Format: PDF
- Size: 480.1 KB