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Comparison of Open-Source Linear Programming Solvers

Gearhart, et.al., Sandia National Labs, Comparison of Open-Source Linear Programming Solvers, 2013, here. I am thinking I will start off with Google or maybe GNU for NIMO. Looks like all roads lead to CPLEX in the long run. The idea is to fit all the Fed historical for the interest rate and credit  risk of the aggregate USD  BHC Assets and Liabilities with high enough degree interpolation polynomials  that the modeling error is effectively zero for  quarterly simulation over several years. We will fit the data to match the agg amounts reported, but we bypass the ability to forecast for the moment. Then we can run the forward optimization using the error free models from one historical time point t1 to another historical time point t2.  Once we know the optimal capital allocation for the period we can run the p&l explanatories back from t2 to t1 to do the attribution. If we can get the BHC portfolio breakdown for the period (t1, t2) then we might be able to make attribution observations that hold some interest on a per BHC (bank) basis.

When developing linear programming models, issues such as budget limitations, customer requirements, or licensing may preclude the use of commercial linear programming solvers. In such cases, one option is to use an open-source linear programming solver. A survey of linear programming tools was conducted to identify potential open-source solvers. From this survey, four open-source solvers were tested using a collection of linear programming test problems and the results were compared to IBM ILOG CPLEX Optimizer (CPLEX) [1], an industry standard. The solvers considered were: COIN-OR Linear Programming (CLP) [2], [3], GNU Linear Programming Kit (GLPK) [4], lp_solve [5] and Modular In-core Nonlinear Optimization System (MINOS) [6]. As no open-source solver outperforms CPLEX, this study demonstrates the power of commercial linear programming software. CLP was found to be the top performing open-source solver considered in terms of capability and speed. GLPK also performed well but cannot match the speed of CLP or CPLEX. lp_solve and MINOS were considerably slower and encountered issues when solving several test problems.

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