[HN Gopher] Optimization solvers: missing link for fully open-so...
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Optimization solvers: missing link for fully open-source energy
system modeling
Author : eisa01
Score : 61 points
Date : 2022-04-30 08:04 UTC (14 hours ago)
(HTM) web link (drive.google.com)
(TXT) w3m dump (drive.google.com)
| twobitshifter wrote:
| I've been impressed with Google's OR-Tools CP-SAT solver which is
| free to use. I think I will need a good reason to us something
| other than a satisfiability solver on most problems. It's a bit
| like the Pareto principle. You can spend a fraction of the time
| running a sat solver and get most of the benefit of trying to
| find the optimal result.
| jvanderbot wrote:
| Where's Scip? it's performance relative to CPLEX was pretty good
| for the problems I threw at it.
| SparseRunner wrote:
| HiGHS for MIP is meaningfully faster than than SCIP after 18
| months, and will get a lot better. SCIP's native LP solver is
| just simplex (and slower than HiGHS). For these problems you
| need interior point, and HiGHS is much the best open-source
| interior point solver for them.
| j2kun wrote:
| I do datacenter optimization at Google and SCIP is ~2 orders of
| magnitude slower than Gurobi for our problems.
| quanto wrote:
| >even the current interior point implementation in HiGHS can be
| unacceptably slow relative to Gurobi (60-100 times slower).
| Considering that even Gurobi requires a couple of days to solve
| huge practical problems illustrates that the use of current open
| source solvers is totally impractical. The aim of this proposal
| is to identify key solver enhancements in the short, medium and
| long term that will help to bridge the significant gap in
| performance between HiGHS and the major commercial solvers.
|
| It's a great need in the scientific community. Gurobi is the
| leading commercial solution with a strict license and a high
| price tag. As the proposed open-source project is only focused on
| linear programming (as opposed to a general nonlinear
| optimization), the goal may as well be achievable. Best wishes
| for the authors.
| SparseRunner wrote:
| Thanks. Matching Gurobi is not feasible, but HiGHS wants those
| who depend on open-source solvers to be able to work with
| bigger models than is currently possible. Once HiGHS has a good
| interior point solver (for QP) - the main aim of this proposal
| - the vision is to develop a nonlinear programming solver.
| eisa01 wrote:
| PDF embed not working on Safari
|
| Main page: https://pypsa-meets-africa.github.io/highs.html
| [deleted]
| rwlincoln wrote:
| I am surprised not to see any mention of the OSQP (Operator
| Splitting Quadratic Program) solver. It is the most impressive
| open source solver of this type that I have seen published in
| recent years. It appears to have been developed as a
| collaboration between Princeton, ETH Zurich, Oxford, Stanford and
| some other prestigious names. The benchmarks show that it
| compares favorably with leading proprietary solvers:
|
| https://github.com/osqp/osqp_benchmarks
|
| The problem described seems to be an ideal use-case for Machine
| Learning. The MATPOWER Optimal Scheduling Toolkit (MOST) can
| already solve:
|
| "a stochastic, security-constrained, combined unit-commitment and
| multiperiod optimal power flow problem with locational
| contingency and load-following reserves, ramping costs and
| constraints, deferrable demands, lossy storage resources and
| uncertain renewable generation."
|
| Much more and it becomes a global optimization problem where you
| can never really be sure you are not just stuck in a local
| optimum. The L2RPN (Learning to Run a Power Network) challenge,
| from RTE-France, is the most interesting effort I have seen
| applying Machine Learning to energy system management.
|
| https://l2rpn.chalearn.org/
|
| https://github.com/rte-france/l2rpn-baselines
|
| The competition has been renewed for 2022 and has been accepted
| for the IEEE World Congress on Computational Intelligence in
| July.
|
| https://wcci2022.org
| algo_trader wrote:
| Can you recommend a go-to library to start solving a charging
| network problem?
|
| The domain is somewhat unique since our charging points are
| mobile and stochastic, but charging demand is scheduled in
| advance
| wenc wrote:
| I'm in the optimization space and have never heard of this.
| Thanks. I recognize many of the names behind it.
|
| I think part of the reason it's not more popular is because QPs
| aren't the most popular problem type. They're used in MPC
| problems and any number of L2-loss function problems like ML
| problems, but these already have custom methods for solving the
| QP. Doesn't meant they can't adopt a standard high performance
| solver -- I think this is very promising.
|
| Also I'm not sure if there's any political issues that limits
| them from listing this on COIN OR. That's usually most folks go
| to site for discovering new solvers.
| thesz wrote:
| The problem is not solution per se, but scalable solution.
| jethkl wrote:
| Yes to this! However, a while ago I tested OSQP, but I found
| low precision and the speed didn't justify using it over other
| solvers. The project remains on my radar due to the strength of
| the development team -- amazing group -- and knowing that
| numerical solvers can really shine in one domain while they
| struggle in others.
|
| Another pair of projects that I find useful are ECOS [1] and
| CVXPY [2]. CVXPY makes head-to-head comparisons of solvers
| (including ECOS and OSQP) trivial.
|
| [1] https://web.stanford.edu/~boyd/papers/ecos.html
|
| [2] https://www.cvxpy.org
| [deleted]
| ggm wrote:
| Not everyone wants to optimise energy to the same outcome. Some
| bad actors are optimising for pure profit and screw the
| environment, not public utility function outcomes.
| ransom1538 wrote:
| If you are out there and are great with solvers - I would look to
| water resource management consulting too. EG:
| http://www.ecorpconsulting.com/marketsector/WaterResources/i...
| SparseRunner wrote:
| Thanks - from HiGHS
| j2kun wrote:
| There's a good reason Gurobi is so expensive, and the company
| hires so many stellar optimization experts. Building a top-tier
| solver is hard, and short of a paradigm shift I don't see this as
| a realistic timeline given the low funding they're asking for,
| and what I've heard about previous attempts to match Gurobi with
| far more funding.
| SparseRunner wrote:
| Throwing money and people at solver projects is not the way to
| succeed. Get and keep the right 1-2 people, and HiGHS has
| already shown what is possible.
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