High-performance MILP Solver—an Advanced Tool With Proven Performance for Efficient and Cost Effective Optimization


Published 09/01/2024 By NAG

MILP featuring modern branch-and-bound techniques, flexible modelling utilities, and various programming languages and OS support

The recent update of the NAG Optimization Modelling Suite saw the introduction of a Mixed Integer Linear Programming (MILP) solver. With this advanced solver, users can solve complex combinatorial optimization problems involving integer variables more efficiently and effectively. The MILP solver has undergone rigorous testing and benchmarking, and is proven in terms of performance and reliability. It implements a branch-and-bound framework with modern techniques including cut generation and primal heuristics, equipped with an effective preserving component that can significantly reduce problem size and solve time.

By integrating this MILP solver into our suite, we are providing our clients with access to state-of-the-art optimization tools that can help them make better decisions in real-time and optimize their operations, leading to improved business outcomes.

Linear programming in which some or all the variables are restricted to be integers is one of the fundamental mathematical optimization techniques that are widely used in many practical Operational Research (OR) problems across various industries, including:

  • Supply chain
  • Electrical power
  • Finance
  • Workforce
  • Transportation
  • Retail
  • Telecommunications

NAG’s MILP solver is accessed via the Optimization Modelling Suite (delivered via the NAG Library) in Mark’s 29.3 and onwards. Contact us to see if your organization has a licence covering the solver’s use or take a 30-day no obligation trial. If you’d like to chat to us about your optimization challenges, we’d be happy to schedule a call with the optimization team.

    Please fill out all of the following questions





    What solvers are you interested in trying? (multiple choice)

    By clicking the button below you agree to our Privacy Policy

    This will close in 20 seconds