A Python package for creating and solving constrained randomization problems.
-
Updated
Oct 14, 2024 - Python
A Python package for creating and solving constrained randomization problems.
The most powerful and extensible way to control the output of large language models.
Solving the two-dimensional strip packing problem, using several combinatorial decision making and optimization approaches: Constraint Programming, Boolean SATisfiability, Satisfiability Modulo Theory; Integer Linear Programming.
Linear Program Solver: Simplex methods are used to solve any linear program (with sensitivity analysis option for constraints)
A demonstration of perturbation of data
Describe processes as type transformations, with inference that supports subtypes and parametric polymorphism. Create and query corresponding transformation graphs.
Simple Horn Clause Reasoner
Repo for 1CK00 Transport and Distribution TUe
Solving minesweeper as a Constraint Satisfaction Problem
Code made for Constraint Programming classes, similar with the 8 queens problem, analyzing solutions, pruning and use of an heuristic to optimize our code
Add a description, image, and links to the constraint topic page so that developers can more easily learn about it.
To associate your repository with the constraint topic, visit your repo's landing page and select "manage topics."