Algorithms for
multi-commodity flow problems
Algorithms for
multi-commodity flow problems
Flowty offer unique IP to logistics businesses
Flowty offer unique IP to logistics businesses
Precision
Precison
Speed
Scale
The fastest multi-commodity flow solver in the world
Flowty has built a set of breakthrough algorithms that redefine scale, speed, and efficiency in middle-mile logistics.
It is available now for acquisition.
Core solver
Flowty core solver is a mixed integer programming solver that solves network optimisation problems.
Flowty core solver is a mixed integer programming solver that solves network optimisation problems.
Flowty core solver is a mixed integer programming solver that solves network optimisation problems.
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Multi-commodity flow solver
Multi-commodity flow solver
Multi-commodity flow solver
Based on column generation technology, this specialised solver targets the optimisation of supply chain networks.
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Resource constrained shortest path solver
A stand alone solver for finding minimum cost paths in large graphs.
A stand alone solver for finding minimum cost paths in large graphs.
A stand alone solver for finding minimum cost paths in large graphs.
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The research behind our technology
Flowty's foundational research has tackled some of the most challenging variants of multi-commodity flow problems, which are so complex that they are typically out of reach for general-purpose solvers.
Flowty's highly parallel pull labelling algorithm for the resource constrained shortest path problem
The resource constrained shortest path problem (RCSPP) is a key subproblem in many decomposition approaches. This work presents a parallel pull labelling algorithm that improves scalability and parallelisation significantly.
Path-based multi-commodity flow solver
The Flowty multi-commodity flow solver is grounded in deep academic insight into the structure and complexity of multi-commodity flow problems.
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A proven legacy in column generation performance
Column generation has long been the dominant technique for solving complex network optimisation problems. Our team has helped define its modern evolution, combining theoretical depth with record-breaking practical performance.
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The research behind our technology
Flowty's foundational research has tackled some of the most challenging variants of multi-commodity flow problems, which are so complex that they are typically out of reach for general-purpose solvers.
Path-based multi-commodity flow solver
The Flowty multi-commodity flow solver is grounded in deep academic insight into the structure and complexity of multi-commodity flow problems.
Read more
Read more
A proven legacy in column generation performance
Column generation has long been the dominant technique for solving complex network optimisation problems. Our team has helped define its modern evolution, combining theoretical depth with record-breaking practical performance.
Read more
Read more
Flowty's highly parallel pull labelling algorithm for the resource constrained shortest path problem
The resource constrained shortest path problem (RCSPP) is a key subproblem in many decomposition approaches. This work presents a parallel pull labelling algorithm that improves scalability and parallelisation significantly.
