Predictive and Prescriptive Analytics from Excel to your Servers and Cloud
- Tools to Build and Solve Your Models
- Data Mining and Machine Learning
- Optimization - Excel Solver Upgrade
- Monte Carlo Simulation/Risk Analysis
- Use Excel, RASON Modeling, SDKs/APIs
- Wizards, Online Courses, Expert Support
Click the circle-X to get rid of a desktop. You can rearrange the order of the desktop spaces by clicking and dragging them in the order you want. However, you can’t move Desktop 1 or the Dashboard.
Tools to Go from Predictions to Money‑Saving Decisions
Wins for Your Whole Team: Analysts, Developers, Managers
- Tools for Analysts
- Tools for Developers
- Tools for Managers
Tools for Analysts
Want to learn and use data science (predictive analytics) and/or management science (prescriptive analytics)? Use our powerful Excel based tools, RASON modeling language, and our learning resources to get results quickly.
You can even work directly with a developer in your company who doesn't use Excel. Analytic models in our RASON modeling language or in Excel run directly in our SDKs and REST API.
Learn MoreTools for Developers
Want to learn and use data science (predictive analytics) and/or management science (prescriptive analytics)? Use our powerful SDKs from your favorite programming language, and our learning resources to get results quickly.
You can even work directly with a business analyst in your company who uses Excel. Analytic models in our RASON modeling language or in Excel run directly in our SDKs and REST API.
Learn MoreTools for Managers
Want to get results from analytics in months, not years? That's what we do best. Use our powerful software tools and training to get quick wins on your first projects, while you grow analytics expertise in the people you have.
Enable business analysts and developers to work together, to quickly move a project from a prototype (easier in Excel) to production in a server or cloud based application.
Learn MoreStart Your Journey from Business Analyst Pro to Analytics Ninja:
Tutorials - Videos - Webinars - Online Courses for You and Your Team
- Optimization Tutorial
- Simulation/Risk Analysis
Tutorial - Data Mining Tutorial
Optimization Tutorial
Solvers, or optimizers, are software tools that help users determine the best way to allocate scarce resources. Examples include allocating money to investments, or locating new warehouse facilities, or scheduling hospital operating rooms. In each case, multiple decisions need to be made in the best possible way while simultaneously satisfying a number of requirements (or constraints). The 'best' or optimal solution might mean maximizing profits, minimizing costs, or achieving the best possible quality. Here are some representative examples of optimization problems:
- Finance/Investment: Cash management, capital budgeting, portfolio optimization.
- Manufacturing: Job shop scheduling, blending, cutting stock problems.
- Distribution and Networks: Routing, truck loading, fleet scheduling.
Simulation/Risk Analysis Tutorial
Quantitative risk analysis is the practice of creating a mathematical model of a project or process that explicitly includes uncertain parameters that we cannot control, and also decision variables that we can control. Monte Carlo simulation explores thousands of possible scenarios, and calculates the impact of the uncertain parameters and the decisions we make on outcomes that we care about -- such as profit and loss, investment returns, environmental results and more. Industries where simulation and risk analysis are heavily used include:
- Pharmaceuticals: Modeling R&D and clinical trials
- Oil & Gas: Modeling drilling projects
- Insurance: Modeling frequency and types of claims
Data Mining Tutorial
Data mining software tools help users find patterns and hidden relationships in data, that can be used to predict behavior and make better business decisions. A machine learning algorithm 'trained' on past observations can be used to predict the likelihood of future outcomes such as customer 'churn' or classify new transactions into categories such as 'legitimate' or 'suspicious'. Other methods can be used uncover 'clusters' of similar observations, or find associations among different items. Common applications include:
- Financial Services: Fraud detection, good vs. bad credit risks
- Direct Marketing: Segmentation to improve response rates
- Electoral Politics: Identifying 'most persuadable' voters
Hear what some of our customers are saying
- The Premium Solver Platform with Xpress Solver engine has been a huge asset to us. We have been able to utilize the solver’s capability to run extremely complex models of our distribution network uncovering large savings; our first project uncovered nearly $1MM in savings.
- ...Then I discovered Solver and all the stuff I had done before after months of programming and sweat was there at my fingertips. The package seemed to go way beyond my wildest dreams. And all the other little extra bits were there as well at the click of a button - non-negative and integer coefficients, constraints, and some other bits I have yet to use. And the thing just works! ...Senior Scientist, Plant and Food Research Co, New Zealand
- The Frontline Premium Solver was very helpful in solving a large water reuse optimization problem for one of our manufacturing plant. It was also very easy to integrate with Excel.
Ready to get started?
Use a full featured version of Analytic Solver software (with model/data size limits, enough for all examples) for 15 days, free of charge.
Welcome to OpenSolver, the Open Source linear, integer and non-linear optimizer for Microsoft Excel.
The latest stable version,OpenSolver 2.9.0(12 Jan 2018) is available for download; this adds the SolveEngine from Satalia as a solver. Refer to the release blog for the new 2.7, 2.8, 2.8.3,2.8.4, 2.8.5 & 2.8.6 improvements. View all releases.
OpenSolver for Google Sheets; see our dedicated OpenSolver for Google Sheets page for more info on the Google Sheets versions of OpenSolver.
COIN-OR Cup Winner: We are pleased to announce that OpenSolver is the winner of the 2011 INFORMS COIN-OR Cupsponsored by IBM. Thanks, COIN-OR, for this honour.
OpenSolver is an Excel VBA add-in that extends Excel’s built-in Solver with more powerful solvers. It is developed and maintained by Andrew Mason and students at the Engineering Science department, University of Auckland, NZ. Recent developments are courtesy of Jack Dunn at MIT.
OpenSolver provides the following features:
- OpenSolver offers a range of solvers for use in Excel, including the excellent, Open Source, COIN-ORCBC optimization engine which can quickly solve large Linear and Integer problems.
- Compatible with your existing Solver models, so there is no need to change your spreadsheets
- No artificial limits on the size of problem you can solve
- OpenSolver is free, open source software.
As well as providing replacement optimization engines, OpenSolver offers:
- A built-in model visualizer that highlights your model’s decision variables, objective and constraints directly on your spreadsheet
- A fast QuickSolve mode that makes it much faster to re-solve your model after making changes
- An algorithm to build and update the model only using information present on the sheet
- A modelling tool that we think improves on the built-in Solver window
OpenSolver has been developed for Excel 2007/2010/2013/2016 (including the 64bit versions) running on Windows, and supports Excel for Mac 2011 on Mac OS X, with limited support for Excel for Mac 2016. We currently test against Excel 2010/2013/2016 on Windows 7 and Windows 10, and Excel 2011/2016 on OS X 10.7 through 10.11. Note that we do not check our code against other versions of Excel or Windows/Mac than these. This means we cannot guarantee that the latest release will work on old versions. However, please give it a go and let us know of any problems so we can fix them.
You can download OpenSolver.zip (which is hosted on our Open Solver Source Forge site). Version details (and dates of updates) are shown on the blog page.
SolverStudio is a free alternative to OpenSolver that is better suited to larger problems. Available as a free download, SolverStudio lets you use Excel to edit, save and solve optimisation models built using modelling languages such as the Python-based PuLP, AMPL, GAMS, GMPL, COOPR/Pyomo and Gurobi’s Python interface. The latest release allows GAMS and AMPL modesl to be solved in the cloud using the excellent free NEOS servers. The SolverStudio interface is fully Excel-based, with the model being edited and run from Excel and stored inside the Excel file. This approach provides a much better modelling solution for complex optimisation problems. Check out the screen shots to see how it works. SolverStudio is much better and faster for large problems. However, OpenSolver is still a great tool for simpler models, or spreadsheets that must be compatible with the built-in Solver.
OpenSolver is being developed by Andrew Mason in the Department of Engineering Science at the University of Auckland, and Iain Dunning. Kat Gilbert also made valuable contributions to the code while working as a summer student. Current development is lead by Jack Dunn from MIT. Development of OpenSolver is made easier by the excellent Excel Name Manager which displays all the hidden worksheet names used to store an optimization model.
OpenSolver is released as open source code under the GPL. This program is distributed in the hope that it will be useful, but without any warranty; without even the implied warranty of merchantability or fitness for a particular purpose. OpenSolver uses a range of solvers, information on these is available here.
Citing OpenSolver: Continued development of OpenSolver is only possible if we can demonstrate its impact. If you are publishing work that uses OpenSolver, please cite both this opensolver.org website and this paper:
Mason, A.J., “OpenSolver – An Open Source Add-in to Solve Linear and Integer Progammes in Excel”, Operations Research Proceedings 2011, eds. Klatte, Diethard, Lüthi, Hans-Jakob, Schmedders, Karl, Springer Berlin Heidelberg
pp 401-406, 2012, http://dx.doi.org/10.1007/978-3-642-29210-1_64, http://opensolver.org
pp 401-406, 2012, http://dx.doi.org/10.1007/978-3-642-29210-1_64, http://opensolver.org
Latex Reference
@INCOLLECTION{OpenSolver,
author = {Mason, AndrewJ},
title = {OpenSolver – An Open Source Add-in to Solve Linear and Integer Progammes
in Excel},
booktitle = {Operations Research Proceedings 2011},
publisher = {Springer Berlin Heidelberg},
year = {2012},
editor = {Klatte, Diethard and Lathi, Hans-Jakob and Schmedders, Karl},
series = {Operations Research Proceedings},
pages = {401-406},
note = {http://opensolver.org},
doi = {10.1007/978-3-642-29210-1_64},
isbn = {978-3-642-29209-5},
language = {English},
url = {http://dx.doi.org/10.1007/978-3-642-29210-1_64}
}
author = {Mason, AndrewJ},
title = {OpenSolver – An Open Source Add-in to Solve Linear and Integer Progammes
in Excel},
booktitle = {Operations Research Proceedings 2011},
publisher = {Springer Berlin Heidelberg},
year = {2012},
editor = {Klatte, Diethard and Lathi, Hans-Jakob and Schmedders, Karl},
series = {Operations Research Proceedings},
pages = {401-406},
note = {http://opensolver.org},
doi = {10.1007/978-3-642-29210-1_64},
isbn = {978-3-642-29209-5},
language = {English},
url = {http://dx.doi.org/10.1007/978-3-642-29210-1_64}
}
Footnote
The Excel Solver is a product developed by Frontline Systems for Microsoft. OpenSolver has no affiliation with, nor is recommend by, Microsoft or Frontline Systems. All trademark terms are the property of their respective owners.