Design and Use of the Microsoft Excel Solver

@article{Fylstra1998DesignAU,
  title={Design and Use of the Microsoft Excel Solver},
  author={Daniel H. Fylstra and Leon S. Lasdon and John Watson and Allan D. Waren},
  journal={Interfaces},
  year={1998},
  volume={28},
  pages={29-55}
}
In designing the spreadsheet optimizer that is bundled with Microsoft Excel, we and Microsoft made certain choices in designing its user interface, model processing, and solution algorithms for linear, nonlinear, and integer programs. We describe some of the common pitfalls users encounter and remedies available in the latest version of Microsoft Excel. The Solver has many applications and great impact in industry and education. 

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References

SHOWING 1-10 OF 42 REFERENCES

Practical Management Science Spreadsheet Modeling and Applications

This modern, applied introduction to the most useful quantitative tools in business emphasizes optimization, simulation and decision analysis and covers the entire modeling process with the use of spreadsheets.

Modeling Optimization Problems in the Unstructured World of Spreadsheets

Practical Management Science

The essentials resource website, whose access is available with every new book, includes links to the following add-ins: the Palisade Decision Tools Suite (@RISK, StatTools, PrecisionTree, TopRank, RISKOptimizer, NeuralTools, and Evolver); and SolverTable, which allows to do sensitivity analysis.

Design and Testing of a Generalized Reduced Gradient Code for Nonlinear Programming

A Generalized Reduced Gradient algorithm for nonlinear programming, its implementation as a FORTRAN program for solving small to medium size problems, and some computational results are described.

AMPL: A Modeling Language for Mathematical Programming

An efficient translator is implemented that takes as input a linear AMPL model and associated data, and produces output suitable for standard linear programming optimizers.

Introductory Management Science

This book discusses linear programming, Probabilistic models: simulation decision theory and decision trees project management - PERT and CPM inventory models with probabilistic demand queuing models forecasting and introduction to non-linear programming.

GAMS, a user's guide

JuMP is an open-source modeling language that allows users to express a wide range of ideas in an easy-to-use manner.

Managerial spreadsheet modeling and analysis

The nature of managerial problem solving linear programming - simple models postoptimal linear programming analysis linear programming - combination models and reports allocation models routing

Solving Large Sparse Nonlinear Programs Using GRG

A feasibility-retaining GRG algorithm for large sparse nonlinear programs of general form, enhanced by heuristics which aid in basis selection, combatting degeneracy, dynamic tolerance adjustment, and predicting Newton failures is described.

Finding a Useful Subset of Constraints for Analysis in an Infeasible Linear Program

This article addresses the problem of finding IISs having few rows in infeasible linear programs using a modified version of MINOS 5.4 called MINOS(IIS).