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Global Optimization pp 155–210Cite as

Disciplined Convex Programming

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Part of the book series: Nonconvex Optimization and Its Applications ((NOIA,volume 84))

Summary

A new methodology for constructing convex optimization models called disciplined convex programming is introduced. The methodology enforces a set of conventions upon the models constructed, in turn allowing much of the work required to analyze and solve the models to be automated.

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Authors and Affiliations

  1. Department of Electrical Engineering, Stanford University, USA

    Michael Grant, Stephen Boyd & Yinyu Ye

  2. Department of Management Science and Engineering, Stanford University, USA

    Yinyu Ye

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  2. Stephen Boyd
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  1. Politecnico di Milano, Italia

    Leo Liberti

  2. COPPE, Universidade Federal do Rio de Janiero, Brasil

    Nelson Maculan

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Grant, M., Boyd, S., Ye, Y. (2006). Disciplined Convex Programming. In: Liberti, L., Maculan, N. (eds) Global Optimization. Nonconvex Optimization and Its Applications, vol 84. Springer, Boston, MA. https://doi.org/10.1007/0-387-30528-9_7

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