meal-scheduler
HiGHS
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meal-scheduler | HiGHS | |
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3 | 3 | |
- | 795 | |
- | 5.7% | |
- | 9.9 | |
- | 2 days ago | |
C++ | ||
- | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
meal-scheduler
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Ask HN: Do you use an optimization solver? Which one? Why? Do you like it?
I use Minizinc in a personal toy project (https://gitlab.com/dustin-space/meal-scheduler), and GECODE or Google's ortools solver at the backend. It's used for meal planning. Unfortunately it's way way slower than I'd hope. I suspect I just have the domain not modeled efficiently. Maybe if I had a few days to put into it, and learn how to properly debug the CSP solver step by step, it might help...
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What is your “I don't care if this succeeds” project?
That sounds like a fun application, both the usage and the implementation.
I wonder if you have any interesting example data-files that could be used with the model, preferable both something small and something larger? Would be fun to test the model locally to see how it behaves.
Notes: I'm assuming here that https://gitlab.com/dustin-space/meal-scheduler/-/blob/master... is the model used.
HiGHS
- Algorithms - Researchers Approach New Speed Limit for Seminal Problem
- HiGHS: High performance open source MILP and QP solver
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Ask HN: Do you use an optimization solver? Which one? Why? Do you like it?
I've been using CBC via python-mip (https://github.com/coin-or/python-mip). It's great because it's got a super clean interface (milp variables/expressions/constraints), the code is quite accessible, and it's low overhead which makes it good for solving many very small problems.
Community sentiment seems to be beginning to shift toward favouring the HiGHS solver (https://github.com/ERGO-Code/HiGHS) over CBC. Something I'm keeping a close eye on.
nextmv seems to pitch itself as a generic solving ("decision automation") platform or something (unclear). But it seems that the only fleshed out product offering is for vehicle routing, based on the docs. Are there plans to offer, for instance, a solver binary that can be used to solve generic problems?
Also all the github repos under https://github.com/nextmv-io are private, so links from docs are 404.
What are some alternatives?
ppp_thing - A poorly written, minimum viable PPPoE client with session handoff between redundant FreeBSD routers
or-tools - Google's Operations Research tools:
electron-browser-shell - A minimal, tabbed web browser with support for Chrome extensions—built on Electron.
OptaPlanner - Java Constraint Solver to solve vehicle routing, employee rostering, task assignment, maintenance scheduling, conference scheduling and other planning problems.
listudy - Listudy - chess training server
osqp - The Operator Splitting QP Solver
Arthur - How to build your own AI art installation from scratch [Moved to: https://github.com/maxvfischer/DIY-ai-art]
csips - A pure-python integer programming solver
singyeong - 신경 - Cloud-native messaging/pubsub with powerful routing
clpz - Constraint Logic Programming over Integers
go-plugin - Golang plugin system over RPC.
exact