[ Tech stack ]
IBM CPLEX
IBM's optimization solver, bundled with CP Optimizer and the OPL modeling language.
IBM ILOG CPLEX Optimization Studio pairs the CPLEX solver (LP, MILP, QP, MIQCP, with simplex, barrier and branch-and-cut) with CP Optimizer, a constraint-programming engine built for scheduling, and the OPL modeling language with its IDE. It integrates with Python (docplex), C++, Java and .NET, and runs as a managed service through Decision Optimization on IBM watsonx.ai or Cloud Pak for Data. It's our choice when a client already runs on IBM tooling, or when a problem mixes combinatorial constraints and linear optimization in the same model.
[ Why IBM CPLEX at Dexon ]
What this technology does well, and why we use it.
Typical usage: Shop-floor scheduling, fleet planning, network and portfolio optimization.
- 01
CPLEX: LP, MILP, QP and MIQCP with simplex, barrier and branch-and-cut.
- 02
CP Optimizer: constraint programming purpose-built for scheduling and sequencing.
- 03
OPL and its IDE: readable models, separate data, side-by-side scenarios.
- 04
Decision Optimization: managed execution on watsonx.ai and Cloud Pak for Data.
[ Complementary technologies ]
The building blocks we often mobilise alongside
A stack rarely exists alone. Here are the technologies Dexon most often pairs with this one, through pipeline habits, usage similarity or internal mastery. Click on a building block to see its scope.
[ Reassurance ]
- 0+
- custom projects delivered
- 30
- engineers, designers, project managers
- 80 %
- from top French schools
- 24 h
- average reply time
[ They trust us ]
More than 100 French and European companies trust us
[ Press ]
They talk about us
Discover what the business and tech press say about us. An outside reading of our work and our innovations.
