Computing in Operations Research Using Julia

References

• Andersson J (2013) A general-purpose software framework for dynamic optimization. Ph.D. thesis, Arenberg Doctoral School, KU Leuven, Department of Electrical Engineering (ESAT/SCD) and Optimization in Engineering Center, Heverlee, Belgium.Google Scholar
• Belotti P, Lee J, Liberti L, Margot F, Wächter A (2009) Branching and bounds tightening techniques for non-convex MINLP. Optim. Methods Software 24(4–5):597–634.Crossref, Google Scholar
• Bezanson J, Karpinski S, Shah VB, Edelman A (2012) Julia: A fast dynamic language for technical computing. Accessed January 29, 2015, http://arxiv.org/abs/1209.5145.Google Scholar
• Bixby RE (2002) Solving real-world linear programs: A decade and more of progress. Oper. Res. 50(1):3–15.Link, Google Scholar
• Bolz CF, Cuni A, Fijalkowski M, Rigo A (2009) Tracing the meta-level: PyPy’s tracing JIT compiler. Proc. 4th Workshop Implementation, Compilation, Optim. Object-Oriented Languages Programming Systems, ICOOOLPS ’09 (ACM, New York), 18–25.Crossref, Google Scholar
• Brooke A, Kendrick D, Meeraus A, Raman R (1988) GAMS: A User’s Guide (Scientific Press, Redwood City, CA).Google Scholar
• Duff IS, Grimes RG, Lewis JG (1989) Sparse matrix test problems. ACM Trans. Math. Software 15(1):1–14.Crossref, Google Scholar
• Fourer R, Orban D (2010) DrAmpl: A meta solver for optimization problem analysis. Comput. Management Sci. 7(4):437–463.Crossref, Google Scholar
• Fourer R, Gay DM, Kernighan BW (1993) AMPL: A Modeling Language for Mathematical Programming, 2nd ed. (Brooks/Cole, Pacific Grove, CA).Google Scholar
• Gay DM (1985) Electronic mail distribution of linear programming test problems. Math. Programming Soc. COAL Newsletter 13:10–12.Google Scholar
• Gay DM (1996) More AD of nonlinear AMPL models: Computing Hessian information and exploiting partial separability. Berz M, Bischof C, Corliss G, Griewank A, eds. Computational Differentiation: Applications, Techniques, and Tools (SIAM, Philadelphia), 173–184.Google Scholar
• Gay DM (1997) Hooking your solver to AMPL. Technical report, Bell Laboratories, Murray Hill, NJ.Google Scholar
• Grant MC, Boyd SP (2013) The CVX users’ guide (release 2.0). Accessed May 1, 2013, http://cvxr.com/cvx/doc/CVX.pdf.Google Scholar
• Hall J (2010) Towards a practical parallelisation of the simplex method. Comput. Management Sci. 7(2):139–170.Crossref, Google Scholar
• Hall J, McKinnon K (2005) Hyper-sparsity in the revised simplex method and how to exploit it. Comput. Optim. Appl. 32(3):259–283.Crossref, Google Scholar
• Harris PMJ (1973) Pivot selection methods of the DEVEX LP code. Math. Programming 5(1):1–28.Crossref, Google Scholar
• Hart WE, Watson J-P, Woodruff DL (2011) Pyomo: Modeling and solving mathematical programs in Python. Math. Programming Comput. 3(3):219–260.Crossref, Google Scholar
• Koberstein A (2005) The dual simplex method, techniques for a fast and stable implementation. Unpublished doctoral thesis, Universität Paderborn, Paderborn, Germany.Google Scholar
• Lattner C, Adve V (2004) LLVM: A compilation framework for lifelong program analysis and transformation. Code Generation Optim., 2004. Internat. Sympos., Palo Alto, CA, 75–86.Crossref, Google Scholar
• Lofberg J (2004) YALMIP: A toolbox for modeling and optimization in MATLAB. Comput. Aided Control Systems Design, 2004 IEEE Internat. Sympos., Taipai, Taiwan, 284–289.Crossref, Google Scholar
• Maros I (2003) Computational Techniques of the Simplex Method (Kluwer Academic Publishers, Norwell, MA).Crossref, Google Scholar
• Mitchell S, O’Sullivan M, Dunning I (2011) Pulp: A linear programming toolkit for python. Accessed May 1, 2013, https://code.google.com/p/pulp-or/.Google Scholar
• Mittelmann H (2013) Benchmarks for optimization software. Accessed April 28, 2013, http://plato.la.asu.edu/bench.html.Google Scholar
• Suhl UH, Suhl LM (1990) Computing sparse LU factorizations for large-scale linear programming bases. ORSA J. Comput. 2(4):325–335.Link, Google Scholar
• van der Walt S, Colbert SC, Varoquaux G (2011) The NumPy array: A structure for efficient numerical computation. Comput. Sci. Engrg. 13(2):22–30.Crossref, Google Scholar