In this work, we propose an hybrid multi-objective optimization design procedure for PI controller tuning. This procedure focuses on reliability-based optimization instances, where Montecarlo methods are used to evaluate quantitatively the performance degradation of a controller, due to unexpected or unmodeled dynamics. The procedure is evaluated on a non-linear Peltier process. The presented r...

Development and deployment of interactive evolutionary multiobjective optimization algorithms (EMOAs) have recently gained broad interest. In this study, first steps towards a theory of interactive EMOAs are made by deriving bounds on the expected number of function evaluations and queries to a decision maker. We analyze randomized local search and the (1+1)-EA on the biobjective problems LOTZ ...

This paper presents a new approach to treat reactive power (VAr) planning problem using multi-objective evolutionary algorithms. Specifically, Strength Pareto Evolutionary Algorithm (SPEA) and Multi-Objective Particle Swarm Optimization (MOPSO) approaches have been developed and successfully applied. The overall problem is formulated as a nonlinear constrained multi-objective optimization probl...

The satellites scheduling mission play an effective role in enhancing the of ground station control and monitoring systems. In this search, SGSEO is re-formulated into a multi-objective optimization task. Therefore, Gravitational Search Algorithm GSA exploited to attain several essential objectives for generating tight scheduling. Moreover, particle swarm model PSO consolidated with novel form ...