IBM ILOG CPLEX Optimization Studio vs. Jupyter Notebook

In my opinon, if the problem is less than 5000 variables, one should try to solve with free available solver rather than directly going for a commercial license of IBM CPLEX Optimization Studio. In my opinion, if the priority is not in terms of solving time with higher number of variables, even then one can go for free solvers like CBC, IPOPT, SCIP. In my opinion, if priority is solving time and number of variables is also high, only in that case one should prefer going for a commercial license.

I would rate it 9/10 while recommending Jupyter Notebook as it offers me a wide range of functionality to operate. It is very well suited for someone who is new to python programming as the user interface helps you build code line by line. I personally have written multiple programs in Python using Jupyter Notebook as it helps me organize long code by breaking it in a structure. Also the ability to write comments using '#' helps a lot to a reader understand the code.

Incentivized

• Linear Programming
• Mixed-Integer Linear Programming
• Non-Linear Convex-Optimization
• Visualization
• Shadow Price Analysis
• Parameter Tuning

• Coding and error correction line by line
• Simple and Effectiveness
• Easy to use for visualisation and presentation of code
• Could be used at any place any time without hassle

Incentivized

• Data handling from different sources like Note Pad, etc.
• Large size of MILP problems.
• Various parameters to set.

• Need more Hotkeys for creating a beautiful notebook. Sometimes we need to download other plugins which messes [with] its default settings.
• Not as powerful as IDE, which sometimes makes [the] job difficult and allows duplicate code as it get confusing when the number of lines increases. Need a feature where [an] error comes if duplicate code is found or [if a] developer tries the same function name.

Incentivized

It's nice to use and with good optimization.

Jupyter is highly simplistic. It took me about 5 mins to install and create my first "hello world" without having to look for help. The UI has minimalist options and is quite intuitive for anyone to become a pro in no time. The lightweight nature makes it even more likeable.

Incentivized

Honestly, to say, I never contacted CPLEX but used its forum to know/clarify any issues I faced.

I haven't had a need to contact support. However, all required help is out there in public forums.

Incentivized

Compared with MATLAB, CPLEX is a more user-friendly and simpler structure for writing models. This one also has a good return on investment.

Jupyter Notebook is unique in that it offers a flexible, lightweight, easy-to-replicate way of organizing your code in a visually intuitive fashion that can be exported in a number of formats. I've found that the broad functionalities available within the notebooks suit a lot of needs I have for EDA, modeling, and data export that makes other software products fairly redundant.

Incentivized

• Better for price.
• Many model parameters/features.
• No visualization.

• Positive impact: flexible implementation on any OS, for many common software languages
• Positive impact: straightforward duplication for adaptation of workflows for other projects
• Negative impact: sometimes encourages pigeonholing of data science work into notebooks versus extending code capability into software integration

Incentivized