Combinatorial generators including combinations, permutations, combinations with replacement, permutations with replacement, cartesian products, and power sets.
E2E Combinatorial Testing Tool
Type-safe combinatorial command-line interface parser
Type-safe combinatorial command-line interface parser
Combinatorial explosion for arrays and trees
Fast Combinatorial Non-negative Least Squares
Combinatorial string generator using spintax syntax
One-wise combinatorial testing generator
A combinatorial grammar for narrative-based projects
Run WebDriver for combinatorial testing
Combinatorial Test Case Generation
ES2015 generator (iterable iterator) for cartesian product. Put combinatorial explosion back in the kennel.
Ultra Mega Enumerator is a lightweight library designed to enumerate various combinatorial objects.
a combinatorial game engine
Various tools for maintaining combinatorial embeddings of network graphs.
Combinatorial/Cartesian Lazzy Set
a PEG combinatorial parser
Typesafe combinatorial data validators for typescript.
Node.js-friendly command-line tool for running PICT-style combinatorial test generation
A simple combinatorial iterator, supporting a stream of combinations.
Quantum-inspired optimization algorithms with swarm-based circuit exploration for combinatorial and constraint problems
Quantum-inspired optimization plugin providing simulated annealing, QAOA, Grover search, dependency resolution, and schedule optimization for combinatorial problems.
COmbinatorial Reachability Testing for asynchronous unit tests
A library containing combinatorial optimization algorithms
Combinatorial tools, functions, and generators.
Create every combination possible of values of 2D collections / iterators.
A flexible, high-performance genetic algorithm library written in Rust
Rust implmementations of combinatronic concepts
Solve any combinatorial game
Combinatorial Game Theory framework
DDO a generic and efficient framework for MDD-based optimization.
Discrete Optimization Global Search framework. Implements various search algorithms that can be found in combinatorial optimization or heuristic search.
Asemantic computation and Church-style isomorphism using combinatory logic.
A Rust implementation of generalized maps (n-dimensional combinatorial topology) for representing meshes, graphs, and complex geometric structures.
A parser for the Lynx declarative modeling language - a statically typed language for expressing combinatorial optimization problems
Optimization module for SciRS2 (scirs2-optimize)
A resolver of combinatorial number-placement puzzles, like Sudoku.
The thing to convert entities from one to other. Idea from Python Trafaret lib in Ruby way.
Combinatory logic parsing and reduction
Knapsacker is a Knapsack (combinatorial opimization) problem solver with Branch and bound algorithm.
A Ruby gem implementing the combinatory logic birds from Raymond Smullyan's To Mock a Mockingbird
In computer science, a disjoint-set data structure, also called a union–find data structure or merge–find set, is a data structure that keeps track of a set of elements partitioned into a number of disjoint (non-overlapping) subsets. It provides near-constant-time operations (bounded by the inverse Ackermann function) to add new sets, to merge existing sets, and to determine whether elements are in the same set. In addition to many other uses (see the Applications section), disjoint-sets play a key role in Kruskal's algorithm for finding the minimum spanning tree of a graph. A disjoint-set forest consists of a number of elements each of which stores an id, a parent pointer, and, in efficient algorithms, a value called the "rank". The parent pointers of elements are arranged to form one or more trees, each representing a set. If an element's parent pointer points to no other element, then the element is the root of a tree and is the representative member of its set. A set may consist of only a single element. However, if the element has a parent, the element is part of whatever set is identified by following the chain of parents upwards until a representative element (one without a parent) is reached at the root of the tree. Forests can be represented compactly in memory as arrays in which parents are indicated by their array index. Disjoint-set data structures model the partitioning of a set, for example to keep track of the connected components of an undirected graph. This model can then be used to determine whether two vertices belong to the same component, or whether adding an edge between them would result in a cycle. The Union–Find algorithm is used in high-performance implementations of unification. This data structure is used by the Boost Graph Library to implement its Incremental Connected Components functionality. It is also a key component in implementing Kruskal's algorithm to find the minimum spanning tree of a graph. Note that the implementation as disjoint-set forests doesn't allow the deletion of edges, even without path compression or the rank heuristic. Sharir and Agarwal report connections between the worst-case behavior of disjoint-sets and the length of Davenport–Schinzel sequences, a combinatorial structure from computational geometry.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.