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IBM ILOG CPLEX Optimization Studio Reviews and Ratings

Rating: 9.7 out of 10
Score
9.7 out of 10

Reviews

2 Reviews

Optimization Excellence with IBM CPLEX Optimization Studio

Rating: 9 out of 10

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

Likelihood to Recommend

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.

VU
Verified User
Employee in Research & Development (5001-10,000 employees)
Vetted Review
IBM ILOG CPLEX Optimization Studio
2 years of experience

Great User-friendly Software for Linear Programming

Rating: 9 out of 10

Use Cases and Deployment Scope

Our organization used IBM CPLEX Optimization Studio for solving large optimization problems in research and in demonstrations to students at the graduate level. We have more than 50 licenses for CPLEX and installed for Research and Laboratory Purposes. CPLEX addresses various business problems such as Integer Programming, Mixed Integer Programming, Quadratic Programming, etc.

Pros

  • Integer programming.
  • Mixed integer programming.
  • Quadratic programming.
  • Multi-objective optimization.

Cons

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

Likelihood to Recommend

It is well suited for solving large-sized, mixed-integer, and integer programming problems. Now, the new version supports for Multi-Objective optimization along with some new algorithms such as Benders Decomposition. It is less appropriate for quadratic programming problems where the objective function is the product of multiple variables. However, it's very easy to code any problem.

VU
Verified User
Professional in Engineering (10,001+ employees)
Vetted Review
IBM ILOG CPLEX Optimization Studio
3 years of experience