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Technical Note—A Duality Theory for Convex Programming with Set-Inclusive Constraints
Author(s) -
A. L. Soyster
Publication year - 1974
Publication title -
operations research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.797
H-Index - 140
eISSN - 1526-5463
pISSN - 0030-364X
DOI - 10.1287/opre.22.4.892
Subject(s) - duality (order theory) , mathematical optimization , linear programming , mathematics , convex analysis , set (abstract data type) , convex set , convex optimization , solution set , convex combination , subderivative , regular polygon , strong duality , feasible region , dual (grammatical number) , convex hull , combinatorics , computer science , optimization problem , art , geometry , literature , programming language

This paper extends the notion of convex programming with set-inclusive constraints as set forth by Soyster [Opns. Res. 21, 1154—1157 (1973)] by replacing the objective vector c with a convex set C and formulating a dual problem. The primal problem to be considered is where the sets {Kj} are convex activity sets, K(b) is a polyhedral resource set, C is a convex set of objective vectors, and the binary operation + refers to addition of sets. Any feasible solution to the dual problem provides an upper bound to (I) and, at optimality conditions, the value of (I) is equal to the value of the dual. Furthermore, the optimal solution of the dual problem can be used to reduce (I) to an ordinary linear programming problem.

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