clpz
golomb-solver
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clpz | golomb-solver | |
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5 | 1 | |
172 | 5 | |
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4.4 | 0.0 | |
about 2 months ago | 8 months ago | |
Prolog | Scala | |
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clpz
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Logic programming is overrated, at least for logic puzzles (2013)
As pointed out in the comments in the article, these kinds of logic puzzles are easier to solve using constraint programming than "regular" logic programming.
For example, see the solution to the Zebra Puzzle here: https://www.metalevel.at/prolog/puzzles which uses CLPZ[^1].
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is it possible to have a reversable operation
None of these are full-fledged programming languages, however. They're limited to problems that lie in the polynomial hierarchy (A class which contains P and NP). Logic programming is generally only used to solve hard problems for which no good algorithm is known. Prolog also sort of fits this niche and it has a bunch of solvers integrated into it. Notably CLPFD which uses https://github.com/triska/clpz for constraint logic programming. Rosette (https://docs.racket-lang.org/rosette-guide/index.html) is another solver-based language. Except it uses lisp syntax (it's embedded in the Racket language). It uses Z3 as a solver (linked above for SMT theories)
- Ask HN: Do you use an optimization solver? Which one? Why? Do you like it?
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What is the difference between constraint solving and constraints programming?
Constraint programming I guess is when one uses a prolog library such as: https://github.com/triska/clpz
golomb-solver
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Ask HN: Do you use an optimization solver? Which one? Why? Do you like it?
CPLEX (by IBM). The documentation can be a bit thin sometimes. But its fast. Most benchmarks place it ahead of the google cloud products.
For fun I made this Golomb ruler solver using cplex: https://github.com/strateos/golomb-solver
What are some alternatives?
prolog-checkers - A Player vs AI game of checkers implemented in Prolog
HiGHS - Linear optimization software
SSI - A Prolog Compiler written in Prolog.
kanren - An extensible, lightweight relational/logic programming DSL written in pure Python
or-tools - Google's Operations Research tools:
osqp - The Operator Splitting QP Solver
python-mip - Python-MIP: collection of Python tools for the modeling and solution of Mixed-Integer Linear programs
optaplanner-quickstarts - Mirror of https://github.com/apache/incubator-kie-optaplanner-quickstarts
csips - A pure-python integer programming solver
OptaPlanner - Java Constraint Solver to solve vehicle routing, employee rostering, task assignment, maintenance scheduling, conference scheduling and other planning problems.