4 ms·

What are you trying to do? Show that deliveries can be made or minimize the cost? If you’re minimizing the cost, shouldn’t this be formulated as an optimizatio

What are you trying to do? Show that deliveries can be made or minimize the cost? If you’re minimizing the cost, shouldn’t this be formulated as an optimization problem?

jvanderbot 7y ago
Yes. That's a MILP. And if we think SAT solvers are useful and underused, wait till you start working with MILP solvers.
- nickpsecurity 7y ago
  I think it was this year I learned they exist. They told me a few to check out. I still don't have a list of applications. What areas were you thinking about when you said underused?
- shaklee3 7y ago
  Yes, yes, yes. I've made this comment a few times on here but tools like MIP solvers are vastly unknown since they didn't take on a sexy name when they started out. However, they can outperform most heuristic based algorithms, and even solve some of the largest problems. It's how the NFL makes their schedules oh, and you can imagine how complicated that is.
  - new4thaccount 7y ago
    Fun fact. Most power grids in the developed world are run off of some of the largest MILP and LP problems. We're talking about millions of constraints to commit units and hundreds of thousands to dispatch them. These run around the clock 24/7. I've only recently learned about SAT type solvers as MILP/LP problems are very fast and globally optimal, unlike things like A* or Genetic Algorithms. I think GA's are cool because you can write one in less than 1/2 page of Python, where MIP solvers are usually large black-box C codesets (Ex: GLPK, CPLEX, GUROBI, XPRESS, Open-Solver).
    - jvanderbot 7y ago
      GA does not belong anywhere near real problems. They are toy solutions with zero guarantees. Fun to code though!
      - new4thaccount 7y ago
        Sadly, I've mostly come to the same conclusion in that I at least need a MIP Gap to tell me how far I am from the optimal solution. My only issue with LP and MILP solvers is scalibility. You have none! Multicore doesn't really seem to help any.
- svd4anything 7y ago
  Ssshhh ... Stop telling everyone. I have rewritten various problems as MILP it finds a solution and people think I’m smart! My favorite MILP is commercial and perhaps somewhat obscure for general population - Mosek. Any recommendations in regards to other good options? perhaps open source that might be in same or better league.
  - throwawaymath 7y ago
    Gurobi, CPLEX and XPRESS are the obvious commercial ones. GLPK and Cbc will also do MILP. For more information, see this page: http://plato.asu.edu/guide.html http://plato.asu.edu/guide.html
    - svd4anything 7y ago
      Thank you so much. Very nice collection of information.
sudhirj 7y ago
Cost minimisation, so yes, it is an optimisation problem, and I haven’t heard of MILPs, will check them out. Is that a Prolog style constraint solver? And would it support dynamic constraints, where some choices will render others impossible (inventory / bandwidth exhaustion)?

What are you trying to do? Show that deliveries can be made or minimize the cost? If you’re minimizing the cost, shouldn’t this be formulated as an optimization problem?

jvanderbot 7y ago

Yes. That's a MILP. And if we think SAT solvers are useful and underused, wait till you start working with MILP solvers.

nickpsecurity 7y ago
I think it was this year I learned they exist. They told me a few to check out. I still don't have a list of applications. What areas were you thinking about when you said underused?
shaklee3 7y ago
Yes, yes, yes. I've made this comment a few times on here but tools like MIP solvers are vastly unknown since they didn't take on a sexy name when they started out. However, they can outperform most heuristic based algorithms, and even solve some of the largest problems. It's how the NFL makes their schedules oh, and you can imagine how complicated that is.
- new4thaccount 7y ago
  Fun fact. Most power grids in the developed world are run off of some of the largest MILP and LP problems. We're talking about millions of constraints to commit units and hundreds of thousands to dispatch them. These run around the clock 24/7. I've only recently learned about SAT type solvers as MILP/LP problems are very fast and globally optimal, unlike things like A* or Genetic Algorithms. I think GA's are cool because you can write one in less than 1/2 page of Python, where MIP solvers are usually large black-box C codesets (Ex: GLPK, CPLEX, GUROBI, XPRESS, Open-Solver).
  - jvanderbot 7y ago
    GA does not belong anywhere near real problems. They are toy solutions with zero guarantees. Fun to code though!
    - new4thaccount 7y ago
      Sadly, I've mostly come to the same conclusion in that I at least need a MIP Gap to tell me how far I am from the optimal solution. My only issue with LP and MILP solvers is scalibility. You have none! Multicore doesn't really seem to help any.
svd4anything 7y ago
Ssshhh ... Stop telling everyone. I have rewritten various problems as MILP it finds a solution and people think I’m smart! My favorite MILP is commercial and perhaps somewhat obscure for general population - Mosek. Any recommendations in regards to other good options? perhaps open source that might be in same or better league.
- throwawaymath 7y ago
  Gurobi, CPLEX and XPRESS are the obvious commercial ones. GLPK and Cbc will also do MILP. For more information, see this page: http://plato.asu.edu/guide.html http://plato.asu.edu/guide.html
  - svd4anything 7y ago
    Thank you so much. Very nice collection of information.

sudhirj 7y ago

Cost minimisation, so yes, it is an optimisation problem, and I haven’t heard of MILPs, will check them out. Is that a Prolog style constraint solver? And would it support dynamic constraints, where some choices will render others impossible (inventory / bandwidth exhaustion)?