optimization models have been used to support decision making in production planning for a long time. however, several of those models are deterministic and do not address the variability that is present in some of the data. robust optimization is a methodology which can deal with the uncertainty or variability in optimization problems by computing a solution which is feasible for all possible ...

Bioventing is a widely recognized technique for the remediation of petroleum hydrocarbon-contaminated soil. In this study, objective was to identify an optimal mathematical model that balances accuracy and ease implementation. A comprehensive review various models developed bioventing conducted wherein advantages disadvantages each were evaluated compared regarding different numerical methods u...

One of the main problems of car-like robot is robust path following in the presence of sliding effect. To tackle this problem, a robust mix H2/H∞ static state feedback control method is selected. This method is the well-known linear robust controller which is robust against external disturbance as well as model uncertainty. In this paper, the path following problem is formulated as linear matri...

The spacecraft simulator robust control through H∞-based linear matrix inequality (LMI) and robust adaptive method is  implemented. The spacecraft attitude control subsystem simulator consists of  a  platform, an air-bearing and a set of four reaction wheels. This set up provides a free real-time three degree of freedom rotation. Spacecraft simulators are applied in upgrading and checking the c...

In this paper, the main idea is to compute the robust regression model, derived by experimentation, in order to achieve a model with minimum effects of outliers and fixed variation among different experimental runs. Both outliers and nonequality of residual variation can affect the response surface parameter estimation. The common way to estimate the regression model coefficients is the ordinar...