The transformation from desktops and servers to devices and cloud services—the Internet of things (IoT)—is well underway. A key problem facing IoT applications is their increasing reliance on estimated data from diverse sources, such as sensors, machine learning, and human computing. Current programming abstractions treat these estimates as if they were precise, creating buggy applications. Exi...

Because of most liner trade is imbalanced, liner operators often need to reposition their empty containers or to lease containers to meet customer’s demand. It is important for liner operators to allocate their empty containers effectively, which implying reducing their leasing cost and the inventory level at ports. In this paper, we consider the ocean transportation problem for empty container...

This paper deals with multicriteria controls for systems coping with polytopic uncertainties. The proposed controls are inspired by a Nash strategy for exactly known systems, reformulated as a nonconvex coupling between Semi-Definite Programming problems. The extension to the uncertain case duplicates the Linear Matrix Inequalities for all vertices of the polytope. A new iterative algorithm usi...

The solid transportation problem is an important extension of the traditional transportation problem. Solid transportation problem with uncertain variables as its parameters is called uncertain solid transportation problem. In this paper, the expected-constrained programming for an uncertain solid transportation problem is given based on uncertainty theory. According to inverse uncertainty dist...

Bargaining with reading habit is no need. Reading is not kind of something sold that you can take or not. It is a thing that will change your life to life better. It is the thing that will give you many things around the world and this universe, in the real world and here after. As what will be given by this theory and practice of uncertain programming, how can you bargain with the thing that h...

In this article, an effective method to control a power system during emergency conditions is presented. Based on Fuzzy Linear Programming (FLP), a new technique is developed to solve the Load Shedding and Generation Reallocation (LSGR) optimization Problem. The objective function consists of terms of load curtailments and deviations in generation schedules. The constraints are power system var...

The classification of fuzzy data is considered as the most challenging areas of data analysis and the complexity of the procedures has been obstacle to the development of new methods for fuzzy data analysis. However, there are significant advances in modeling systems in which fuzzy data are available in the field of mathematical programming. In order to exploit the results of the researches on ...

The numerical solution of the problem treated in this paper is an important step within a couple of recently developed controller-design procedures, dealing with multivariable or uncertain systems subject to hard-bounded control signals. We determine the worst case output amplitude of stable systems, excited with an input signal that is bounded in amplitude and rate. In the case of SISO systems...

Most research in robust optimization has so far been focused on inequality-only, convex conic programming with simple linear models for uncertain parameters. Many practical optimization problems, however, are nonlinear and non-convex. Even in linear programming, coefficients may still be nonlinear functions of uncertain parameters. In this paper, we propose robust formulations (see (1) versus (...

We present a technique for approximate robust dynamic programming that is suitable for linearly constrained polytopic systems with piecewise affine cost functions. The approximation method uses polyhedral representations of the cost-to-go function and feasible set, and can considerably reduce the computational burden compared to recently proposed methods for exact robust dynamic programming [Be...