Optimization Excellence with IBM CPLEX Optimization Studio
Use Cases and Deployment Scope
Most used features of this tool are modelling and solving linear and mixed-integer problems with more than 10,000 variables, shadow price analysis and visualization capabilities. Only issue is with non convex optimization capabilities.
Pros
- Linear Programming
- Mixed-Integer Linear Programming
- Non-Linear Convex-Optimization
- Visualization
- Shadow Price Analysis
- Parameter Tuning
Cons
- Non-convex Optimization problems
- In my opinion, difficult to integrate with existing software
- In my opinion, difficult to use for a new user with no modelling background
- High memory hardware required for its usage
- Expensive commercial license
Return on Investment
- Faster computation leading to better internal customer relations
- Able to solve high variable problems with ease
- Anomaly detection became easier within business
Alternatives Considered
Gurobi Optimizer
Other Software Used
Gurobi Optimizer, Jupyter Notebook, PyCharm, Microsoft Visual Studio Code, Postman, Apache Spark, Amazon EMR (Elastic MapReduce), Amazon Elastic Compute Cloud (EC2), Amazon S3 (Simple Storage Service)
