This is a preview. Log in through your library . Abstract Recently Schechter (in a Lehigh University report) formulated two dual linear programming problems over closed convex cones in quite general ...

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 ...

Given probability spaces (Xi, Ai, Pi), i = 1, 2, let M(P1, P2) denote the set of all probabilities on the product space with marginals P1 and P2 and let h be a measurable function on (X1 × X2, A1 ⊗ A2 ...

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 ...

Fuzzy normed linear spaces extend conventional normed spaces by integrating a degree of imprecision through fuzzy set theory, thereby quantifying uncertainty in the measurement of vector magnitude. In ...

Linear semi-infinite programming (LSIP) is a branch of optimisation that focuses on problems where a finite number of decision variables is subject to infinitely many linear constraints. This ...