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:
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.