It helps me a lot. CPLEX is a tool that can kind of visualize your prediction and help you understand the problem better. For example, for every SOS you can just format a model, which could be an inner model or mixed integer model, that can be solved by CPLEX. You can then see the results to verify your idea, or you can modify your idea.

It would be great if it also could handle nonlinear models or non-linearity. That would be a great complement to the software.

I have used it to solve models for our clients, so all the usual mathematical optimization; the benefits it has given me is in terms of business.

There is not much coding overhead to solve multi-dimensional problems. It allows me to just focus on the actual problem and not coding.

It definitely helps because it's a solver, I can just plug in and use. It's a tool that I have to use, basically.

CPLEX is fairly easy to use and it does provide very high quality solutions which make my algorithms run faster and better.

What I'm doing is finding some clusters in a network. I'll build a model and apply  it to CPLEX and find some clusters. I can interpret some useful meanings about that.

I consider CPLEX to be a state-of-the-art tool and I can't compare the power of my algorithms with CPLEX and the impact that it has had on my PhD thesis.

Whenever you do optimization, having a good CP solver or integer programming solver is a necessity. So CPLEX is a tool that I cannot do without.

Not me, but my group members published high-quality papers relying on CPLEX.

We really use CPLEX to get the exact optimal solutions. But for other algorithms, we can just get approximately optimal results.

It helped me because it was just easier to implement complex models. That's it. But if it was a basic model, then I would use another program. It's not worth the complexity.