I guess it depends on what your application is here. Hexaly primarily focuses on Routing, Packing and Scheduling problems, which have strong Combinatorial components. My experience with those type of problems is that…
The main reason why companies might prefer Hexaly is their emphasis on quickly finding high Quality feasible primal solutions.
Amazon has been quite vocal about using Hexaly.
I cant speak for engineers, but as a mathematician I wholeheartedly disagree with everything you claim in your comment. Almost none of the mathematicians that I know care about the optimization aspect of mathematics:…
I would like to learn more about Web development and related knowledge (networking, security). Currently my programming knowledge is primarily system languages+python. I'm thinking of building a few websites / apps from…
This is actually a pretty poor example because we can solve huge TSP instances to optimality in practice (see the concorde solver). There exist many more tricky Combinatorial problems such as packing or covering…
CPlex has shown no progression in the benchmarks in the past years, so it is safe to assume that the number of developers they have employed is either 0 or maybe 1.
I am an academic in the field. A good starting point would be Tobias Achterberg's PhD thesis: "Constraint Integer Programming" It details the implementation of SCIP, which is one of the leading open source solvers, and…
Yes, there are other interior point methods besides the ellipsoid method, and virtually all of them perform better for linear programming. Sometimes, the solvers will use these at the root node for very large models, as…
As other commenters here have mentioned, in discrete optimization there can be a very large gap between efficienct in theory and efficient in practice, and it is very likely that this is the case here too. Linear…
I guess it depends on what your application is here. Hexaly primarily focuses on Routing, Packing and Scheduling problems, which have strong Combinatorial components. My experience with those type of problems is that…
The main reason why companies might prefer Hexaly is their emphasis on quickly finding high Quality feasible primal solutions.
Amazon has been quite vocal about using Hexaly.
I cant speak for engineers, but as a mathematician I wholeheartedly disagree with everything you claim in your comment. Almost none of the mathematicians that I know care about the optimization aspect of mathematics:…
I would like to learn more about Web development and related knowledge (networking, security). Currently my programming knowledge is primarily system languages+python. I'm thinking of building a few websites / apps from…
This is actually a pretty poor example because we can solve huge TSP instances to optimality in practice (see the concorde solver). There exist many more tricky Combinatorial problems such as packing or covering…
CPlex has shown no progression in the benchmarks in the past years, so it is safe to assume that the number of developers they have employed is either 0 or maybe 1.
I am an academic in the field. A good starting point would be Tobias Achterberg's PhD thesis: "Constraint Integer Programming" It details the implementation of SCIP, which is one of the leading open source solvers, and…
Yes, there are other interior point methods besides the ellipsoid method, and virtually all of them perform better for linear programming. Sometimes, the solvers will use these at the root node for very large models, as…
As other commenters here have mentioned, in discrete optimization there can be a very large gap between efficienct in theory and efficient in practice, and it is very likely that this is the case here too. Linear…