This paper addresses the issue of which strong duality holds between parametric robust semi-definite linear optimization problems and their dual programs. In the case of a spectral norm uncertainty ...

Abstract: Duality is one of the most important topics in optimization either a theoretical and algorithmic perspective. Optimization problem usually involved mathematical model. One of the ...

Linear programming is one of the most common optimization techniques. It has a wide range of applications and is frequently used in operations research, industrial design, planning, and the list goes ...

Abstract: We develop a linear ranking function for ordering bipolar fuzzy numbers and study its properties. Using this ranking function, we solve a bipolar fuzzy linear programing problem. Then, we ...

This paper presents the basic concepts of linear programming, which consists in minimizing or maximizing a linear objective function with linear inequality or equality constraints on the variables of ...

Roughly, we will cover the following topics (some of them may be skipped depending on the time available). Linear Programming: Basics, Simplex Algorithm, and Duality. Applications of Linear ...

Perold, André, and R. Meidan. "Optimality Conditions and Strong Duality in Abstract and Continuous Time Linear Programming." Journal of Optimization Theory and Applications 40, no. 1 (May 1983): 61–76 ...

ABSTRACT: The Kuhn-Tucker theorem in nondifferential form is a well-known classical optimality criterion for a convex programming problems which is true for a convex problem in the case when a ...