This paper addresses a robust multi-objective optimization approaches for tuning Generator Excitation PSS system parameters of power systems. The objective function which is a composite of different performance indices corresponding to different disturbances and steady-state operating conditions is then posed as a multi-objective nonlinear optimization problem together with parameters from a gi...

ABSTRACT: The problem of robust design is treated as a bi-objective optimization problem in which the performance mean and variation are optimized and minimized, respectively. A method for deriving a utility function as a local approximation of the efficient frontier is presented and investigated at different locations of candidate solutions, with different ranges of interest, and for efficient...

The goal of robust optimization problems is to find an optimal solution that is minimally sensitive to uncertain factors. Uncertain factors can include inputs to the problem such as parameters, decision variables, or both. Given any combination of possible uncertain factors, a solution is said to be robust if it is feasible and the variation in its objective function value is acceptable within ...

Based on the recent approach of Bertsimas and Sim (2004, 2003) to robust optimization in the presence of data uncertainty, we prove an easily computable and simple bound on the probability that the robust solution gives an objective function value worse than the robust objective function value, under the assumption that only cost coefficients are subject to uncertainty.We exploit the binary nat...

This paper proposes a systematic technique to design multiple robust H∞ controllers. The proposed technique achieves a desired robust performance objective, which is impossible to achieve with a single robust controller, by dividing the uncertainty set into several subsets, and by designing a robust controller to each subset. To achieve this goal with a small number of divisions of the uncertai...

The design of closed-loop logistics (forward and reverse logistics) has attracted growing attention with the stringent pressures of customer expectations, environmental concerns and economic factors. This paper considers a multi-product, multi-period and multi-objective closed-loop logistics network model with regard to facility expansion as a facility location–allocation problem, which more cl...

there are many real problems in which multiple responses should be optimized simultaneously by setting of process variables. one of the common approaches for optimization of multi-response problems is desirability function. in most real cases, there is a correlation structure between responses so ignoring the correlation may lead to mistake results. hence, in this paper a robust approach based ...

A dynamic robust optimization model is established based on the objective of profit maximization to deal with the uncertainty of the problem through formulating a robust linear programming model. An equivalent robust optimization model using duality theory and auxiliary problem principle is obtained which allows the solutions to be derived more efficiently. Following the numerical simulation an...

Many portfolio optimization problems deal with allocation of assets which carry a relatively high market price. Therefore, it is necessary to determine the integer value of assets when we deal with portfolio optimization. In addition, one of the main concerns with most portfolio optimization is associated with the type of constraints considered in different models. In many cases, the resulted p...