Analytic Solver vs. Megaladata

Based on my limited experience and use, and therefore limited global knowledge of the software, I would recommend it especially if the data that will be used as inputs to the model has previously worked on a spreadsheet such as Excel. I would also recommend it to analyze problems of medium and small size. Given the experience I have had when I have used it with large problems, there have been noticeable decreases in the speed of response (which are not associated with the size of the system of equations involved in the calculation). Excellent for processing linear programming models.

Incentivized

• Easy to use and learn.
• Strong optimization platform for business and supply chain problems which can be modeled in Excel
• It can handle multiple objectives and more than 8000 decision variables in a problem.
• Lots of tutorial and examples are available to solve the problem

Incentivized

• On the few occasions when I have used it to deal with problems of optimization of relatively large parameters (with a large number of restrictions and decision variables), the program has been slower, not substantially but slower, than programs such as the WinQsb, even when the latter runs on 32-bit machines and not 64. That has caught my attention, even though it is not a real problem for the uses I give to the program.
• Given my partial function as a university professor, it has been much more effective and practical to use other software, due to the limited options that the educational license associated with the software has.

Incentivized

We believe in building the models in Excel. A limitation with Excel is that Excel Solver can not take more than 200 decision variables with multiple constraints. It is cheap in terms of license and maintenance fees against other softwares which are available in the market.

Incentivized

• - It has allowed finding ways to optimize (minimizing costs or times) the field processes involved in various projects.
• It has even allowed, in specific cases where it was used for that purpose, to optimize the allocation of resources (people) to work in different jobs that present weekly variations of the activity that these people must perform.
• It has allowed the sensitivity analysis of projects to changes in the decision variables related to them, which, and in very dynamic and changing environments, resulted in substantial decreases in money losses.

Incentivized