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 ...

The design of instruments that rely on the interaction radiation with matter for their operation is a quite complex task if our goal to achieve near optimality some well-defined utility fu...

In this work, we report the experimental implementation of a Quantitative Feedback Theory (QFT) based robust controller, designed online using hybrid global optimization and constraint propagation techniques. The hybrid global optimization combines interval global optimization and nonlinear local optimization methods. The constraint propagation techniques are very effective in discarding infeas...

Waterborne Epoxy based coatings were prepared by using a water-borne epoxy resin and a suitable hardener. The formulation and optimization procedure were carried out on the bases of experimental designs by the mixture design technique in which the important paint properties are modeled by using special cubic model. The corrosion behavior of these coatings was investigated using electrochemical ...

Global optimization methods play an important role to solve many real-world problems. Flower pollination algorithm (FP) is a new nature-inspired algorithm, based on the characteristics of flowering plants. In this paper, a new hybrid optimization method called hybrid flower pollination algorithm (FPPSO) is proposed. The method combines the standard flower pollination algorithm (FP) with the par...