OpenSolver for Google Sheets 2.3.0 (2 April 2017)

Today we are releasing an update to OpenSolver for Google Sheets that includes a new solver: the SolveEngine from Satalia

The update will roll out over the next day or so, and you will then be able to access the SolveEngine in the list of available solvers. The first time you use the solver, you will be prompted to enter your SolveEngine API key, which you can obtain by creating an account using the link in the prompt. This is the beta version of the SolveEngine, which will be free during the beta period. After the beta has ended, users will receive 1 hour of free solving time per month. There will be no queuing during the beta, and after the beta there will be a short queuing time for free users.

The SolveEngine is a cloud-based system, similar to NEOS except with more powerful solvers and much shorter queue times. We hope that it will prove a useful and powerful alternative to the other solvers we offer, and have plans to also offer it in OpenSolver for Excel in the coming future.

SolveEngine Overview

The SolveEngine boasts many features that make it a powerful tool for solving a variety of optimisation problems, notably:

  • A single gateway to a portfolio of solvers;
  • Modern optimisation translators and encoding that give access to a wider range of algorithms;
  • No licence to manage and nothing to install;
  • Distributed cloud computation that enables dynamic resource allocation to accommodate complex and large problems;
  • Machine learning which matches the right algorithms to the problems it receives, improving itself over time.

Users of the SolveEngine benefit from :

  • Access to a constantly evolving portfolio of algorithms, designed to solve problems such as:
    • Boolean Satisfiability problem (SAT)
    • Linear programming (LP)
    • Mixed integer linear programming (MILP)
  • Free solving time (1 hour) after account creation;
  • Free Academic usage;
  • Access to cutting-edge algorithms from academia, and in doing so, supporting academics to commercialise and further develop their algorithmic innovations;
  • Direct access to time honored and also newly developed commercial algorithms;
  • Built-in translators, which means that there is no strict limit to the number of problem formats that can accepted by the SolveEngine and allows for human readable inputs such as GLPK to be submitted;
  • The capability of the SolveEngine to run many solvers in parallel using sophisticated pre-processing and pipelining techniques which identify the most promising routes through to solving the problem faster;
  • Submission of various problems and concurrency of problem solving in a scalable manner;
  • Access to a community of optimisation/modelling experts for support.

Optimisation problems exist across the entire spectrum of business, science and engineering. The SolveEngine has already been used to solve many hard computational problems in graph theory, logistics, system verification, BigData and cryptography.

Satalia Overview

Satalia is a spin-out from the UCL Department of Computer Science. Satalia’s team of academics and artificial intelligence experts harness a library of algorithms, hosted in the SolveEngine, to help companies and organisations solve the world’s most difficult problems. In 2016 Satalia was recognised in the elite Gartner Cool Vendors in Data Science list, the only UK company chosen.

Satalia’s commitment to continued innovation in algorithm development underpins the SolveEngine model through which academics and commercial solver developers can deploy their solvers to the SolveEngine to address the current and emerging requirements of industry and research communities. Providing access to state-of-the-art optimisation algorithms, Satalia enables the industry to analyse problems inputs more efficiently and thus to solve their problems more rapidly.

OpenSolver 2.8.6 (6 Mar 2017)

We have released OpenSolver version 2.8.6 which fixes various bugs:

  • We have updated the URL for NEOS so these solvers will work again
  • Made changes to support Gurobi v7
  • Set worksheet calculation in the OpenSolver file to automatic to avoid setting it to manual for the entire Excel session when OpenSolver is loaded. Thanks to the users that reported this issue.
  • Other minor bugfixes

You can get the new version here.

As always, please let us know about any issues you might have, or features you would like to see in future releases!

250k milestone

Today the download odometer rolled past another milestone:

Thanks to all our users and our development team (and most recently Jack Dunn) for supporting OpenSolver for the last 6 years. None of this would have been possible without the solvers from COIN-OR; thanks to John Forrest and Ted Ralphs for the many years of CBC development, without which the OpenSolver project would never have started.


OpenSolver 2.8.5 (3 Nov 2016)

Today we are releasing OpenSolver version 2.8.5 which fixes a bug brought about by the October update to Excel 2016. This bug in Excel prevented clicks on the constraint section of the model creation form in OpenSolver, and there is a workaround in today’s update so that things work as intended.

You can get the new version here.

The release also includes a new feature that a number of users have asked for in the past, which is the ability to use the NOMAD solver to optimize models where the objective and constraints depend on the output of macros. For instance, one user wanted to use the results of a Pivot Table that depended on the variable values in their model, but Pivot Tables are not updated when the sheet is recalculated so this did not previously work with OpenSolver. Another example comes from Judd Larson at the University of Wyoming. Judd’s problem involved optimizing a function that depended on the solution to a series of differential equations, which he was solving using his VBA implementation of an ODE solver. This is not a problem that can be expressed and solved in the traditional way that OpenSolver supports, but is possible to solve now with the new ability to incorporate the macro into the solution process. We are very pleased to offer a solution to a tough problem like this! For more information on how this feature works, please see the new section in the documentation describing this feature.

As always, please let us know about any issues you might have, or features you would like to see in future releases!

OpenSolver 2.8.4 (12 Oct 2016)

We have just released OpenSolver 2.8.4 which fixes a bug in the 2.8.3 release that caused it to crash on the newest versions of Excel (in most cases the Office 365 versions). This release also fixes a bug where the saved solver choice could get corrupted and force you to re-select the solver.

You can download the 2.8.4 release here.

Don’t forget to enable the update checker in OpenSolver if you want to be notified automatically of new updates like this one.

As always, please let us know if you have any feedback or problems.

OpenSolver 2.8.3 (05 Oct 2016)

We are happy today to announce the release of OpenSolver 2.8.3! This is a bugfix release for the 2.8.2 release, but we are also using the occasion to mark the 2.8.x releases as stable. This means 2.8.3 will become the default download for all users and is the recommended version for everyone.

You can download OpenSolver 2.8.3 here.

This update is primarily a bugfix release (the changelog lists around 20 significant fixes) as well as two new features.

The first new feature is extended support for using the solution on the sheet as the starting point for the solver. Passing the solution as a “warm start” to the solver in this way is now supported by all solvers except CBC. This functionality is enabled automatically – if the initial solution on the sheet is feasible, it will be sent to the solver. This can give significant reductions in solve time when solving tough integer problems.

The other big change in this release is our first partial support for Excel 2016 for Mac. This version should work if your version of Excel is at least 15.28. Unfortunately, the VBA support on this version of Excel is very limited, and so it has been very difficult to get OpenSolver working. We do not yet have the full range of functionality running, but we do have some core features working for those that need to use Excel 2016 for Mac or want to help with testing. Right now, the features that we know are working are model creation and manipulation, and solving using the linear solvers (CBC and Gurobi).

There are some major changes in the way Excel 2016 for Mac works that have made our life difficult. The most important of these is that Excel is now sandboxed for security reasons, which makes it harder for us to run the optimization solvers. Currently, the only workaround we have come up with requires you to run an installer after you download OpenSolver that installs the solvers we use on your system so that they can be used by Excel. Unfortunately this means that you will need administrative privileges on your computer to set up OpenSolver if you want to use Excel 2016 on Mac. Please see the installation page for more information about this.

It seems that Excel 2016 for Mac is significantly slower than any other Excel release, which leads to much slower OpenSolver solve times. We can only hope that Microsoft improve its speed in future releases.

We appreciate any feedback you might have on the release, especially in regards to Excel 2016 for Mac. If you do encounter any problems, please either use the “Report Issue” button from inside OpenSolver, or leave a comment here so that we can address the problem.

Fantasy Football – from OpenSolver to Cloud optimiser

This blog by Derek Nelson shows how he built an OpenSolver model for fantasy football that worked well for him. “My optimizer was created using Excel with the Open Solver add-in. This worked for me and the results were good. Namely, I had the highest projected points for my teams at the start of the season in both leagues I played in (the best you can hope for in the draft, in my opinion), and I ended the season by winning one league and placing second in the other.”

Derek has now gone on to create a cloud-based version of this. This work is an interesting optimisation-based project.

OpenSolver for Google Sheets 2.2.1 (25 July 2016)

Today we are releasing OpenSolver for Google Sheets 2.2.1, which is a very minor update with changes to improve our support for larger models.

Any script running in Google Apps Script has a strict 6-minute time limit while running, and is immediately cut off with no feedback if this limit is reached. It can often take longer than this to build the OpenSolver models if they are large, so we save the model-building progress as we go. If the build is stopped early, we can simply resume the solve from where we last saved the progress. Previously, this would occur the next time the “Solve” button was clicked. With this update, the solve is now automatically resumed if it is cut off, meaning that there is no need to click the “Solve” button repeatedly to build larger models piece-by-piece.

The other important change in this release is a new mechanism for saving the progress as we build the model. Previously we used the Google Apps Script CacheService to store the updates, but this limits the saved data to 100 KB which is too small for larger models. This update changes our behaviour to instead save the progress to a new hidden sheet in the workbook, allowing us to save much larger models.

Other minor changes include:

  • A bug where the costs were not loading correctly when resuming the solve has been fixed.
  • Error messages now contain the stack trace for better debugging.

If you already use OpenSolver for Google Sheets, the update will roll out automatically. If you are not yet a user, you can add it to Google Sheets using the link below:

As always, we welcome any feedback or ideas. We are coming up on a big milestone of 10,000 weekly active users for the Google Sheets addon, and are very happy to see that it is proving useful! If you find it useful, we would appreciate if you could rate us in the Chrome Webstore and/or leave a review for others.

Cool OpenSolver Applications

I recently received a nice email from Andrew Trapp, Assistant Professor, School of Business, Worcester Polytechnic Institute. Andrew has been using OpenSolver and SolverStudio in his student projects. He writes:

I’m writing to first of all thank you for the excellent software tools that you make, OpenSolver and SolverStudio, that I have been using and featuring for 4 years now in my optimization courses. They have also been used in a number of “senior design” projects that I have advised (specifically, OpenSolver in conjunction with VBA…)

Andrew’s OpenSolver projects look very interesting, and show how OpenSolver can be used in practical applications. The reports are available online, as follows:


OpenSolver for Google Sheets v2.2.0 (18 April 2016)

Today we are releasing OpenSolver for Google Sheets 2.2.0, which is a minor update with the following changes:

  • We have added support for early stopping in GLPK. If your problem is taking a while to solve and you are satisfied with the quality of the best solution that has been found so far, you can stop the solve and OpenSolver will load this solution into the sheet. To stop a solve early, just click the “Cancel solve and use current best solution” button.
  • When solving a “Target Objective” problem, we now try to minimize the deviation from the target rather than making the target a hard constraint. Previously, if the target was hard or impossible to reach, the solver may have taken a long time to finish. Coupled with the early stopping in GLPK, you can now stop the solve early if you see that the solution is close enough to your desired target. We will be adopting this approach in OpenSolver for Excel in the very near future.

If you already use OpenSolver for Google Sheets, the update will roll out automatically. If you are not yet a user, you can add it to Google Sheets using the link below:

As always, we welcome any feedback or ideas.