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Conic Linear Programming

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Linear and Nonlinear Programming

Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 228))

Abstract

Conic Linear Programming, hereafter CLP, is a natural extension of Linear programming (LP). In LP, the variables form a vector which is required to be component-wise nonnegative, while in CLP they are points in a pointed convex cone (see Appendix B.1) of an Euclidean space, such as vectors as well as matrices of finite dimensions. For example, Semidefinite programming (SDP) is a kind of CLP, where the variable points are symmetric matrices constrained to be positive semidefinite.

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Luenberger, D.G., Ye, Y. (2021). Conic Linear Programming. In: Linear and Nonlinear Programming. International Series in Operations Research & Management Science, vol 228. Springer, Cham. https://doi.org/10.1007/978-3-030-85450-8_6

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