Open Source Linux Algorithms - Page 20

Simple POSIX multithread Ant Colony Optimizer framework currently for solving Vehicle Routing Problem. Supports UDP, file synchronizatoin between computers.

ADTL is an Advanced Data structures Template Library written in C++. it includs sixteen kinds of stl-like contains, such as fibonacci heap,pariring heap,skew heap,avl tree,red-black tree,splay tree,skip list, unrolled linked list and so on.

ANT is a lightweight implementation in C of a kind of artificial neural net called Multilayer Perceptron, which uses the backpropagation algorithm as learning method. The package includes an introductory example to start using artificial neural nets.

ARMR provides a foundation for creating an efficient in-memory database. Its unique list processing structures simplify programming logic and allow the developer to rapidly sort, group, and select data. Give your app a hypercard like capability.

This AS511 driver use functions from the Siemens S5 PLC to modify, observe and watch the PLC software. The functions are running on some CPUs. The functions are only tested on PLC 100U CPU 103. Be careful to use the Software. This software can destroy machines and kill human if you are non careful. Please let me know, if you find a bug.

Some data structures developed in c++ for the 'Algorithms & Data Structures' exam at the Computer Science Department of the University of Bari by Tafuni Vito & Nicola Perrini.

AVL Array is a sequence container (like std::vector or std::list) that allows fast insert/remove AND fast random access. Shiftable Files offers the usual file primitives plus fast insert/remove. Get the latest version via BZR in the Develop section.

A library for fixed point calculation in s15.16, s7.24 and s7.8 format, entirely written in ANSI C for embedded software (with main focus on the Atmel AVR platforms).

This is a program for compute the dimension of the Hochschild homology k-vector spaces of a k-algebra A.

This is an Ada implementation of the Dancing Links X Algorithm as in Donald E. Knuth paper. AdaDLX is used to solve the Eight-Queens puzzle, Sudoku grids and Blocs in Box puzzle.

A Java implementation of a cubic B-spline curve smoothing function. Allows an arbitary number of points with a variable number of dimensions to have a cubic B-spline curve "fitted". Useful in finance for analysing bond or swap yield and discount curves.

Adaptive Simulated Annealing (ASA) is a C-language code that finds the best global fit of a nonlinear cost-function over a D-dimensional space. ASA has over 100 OPTIONS to provide robust tuning over many classes of nonlinear stochastic systems.

AhoCorasickDoubleArrayTrie is a Java implementation of the Aho–Corasick multi-pattern matching algorithm that is optimized using a Double-Array Trie data structure. It is designed for fast keyword scanning across large texts, where you want to search for many patterns simultaneously and efficiently. The core idea is to build an automaton from a dictionary of patterns, then stream through input text to emit matches with minimal overhead. By using a double-array trie representation, the project emphasizes performance and memory efficiency compared to simpler pointer-heavy trie structures, which can matter a lot for large dictionaries or latency-sensitive services. This makes it a strong fit for tasks like content filtering, entity/term spotting, dictionary-based annotation, or high-throughput log/text processing. In short, it’s a specialized, speed-focused library for industrial-strength multi-keyword matching in Java.

The Airs GPT project experiments with Steady State Genetic Programming create agents that play tag. It emphasises co-evolution through competition, and provides the user with some tools to help them visualize what is taking place.

Aleph is both a multi-platform machine learning framework aimed at simplicity and performance, and a library of selected state-of-the-art algorithms.

AlgART Java libraries for processing arrays and matrices are open-source product, distributed under MIT license. So, anyone can use them for free without any restrictions. Main features: 63-bit addressing of array elements (64-bit long int indexes), memory model concept (allowing storing data in different schemes from RAM to mapped disk files), wide usage of lazy evaluations, built-in multithreading optimization for multi-core processors, wide set of image processing algorithms over matrices, etc. - please see at the site. Almost all classes and methods are thoroughly documented via JavaDoc (you may read full JavaDoc at the site).

The goal: to provide implementations of as many algorithms (sorting, searching, ...) and data structures (lists, trees, ...) as possible, accompanied by discussion of big O run time and memory limits and references to sources of further study.

Algorithms is an educational Java repository containing tested solutions to common computer science and programming problems. It covers binary trees, linked lists, strings, bit operations, mathematics, sequences, arrays, sorting, and miscellaneous interview-style exercises. Many categories contain several related problems so learners can compare recurring techniques and data structures. Some problems include more than one implementation, allowing different approaches to be examined side by side. Every solution is accompanied by tests, and part of the repository was developed using test-driven development. Sorting examples include bubble, selection, insertion, merge, and quick sort. The project is intended for algorithm practice, implementation study, and experimentation rather than as a reusable production library.

An algorithm is represented by a .h file and placed under include. (one .header file per algorithm.) The demo program for the algorithm demonstration is placed under src. (one demo per algorithm.) After the program passes correctly, please initiate Pull Requests, the code is verified and stored in the library, and the new algorithm implementation is published in the README. TAB = 4 space. set ts=4 in vim. Graph output format is Graphviz Dot format. (the output format of the graph is in dot of graphviz.)

Algorithms in Python is a collection of algorithm and data structure implementations (primarily in Python) meant to serve as both learning material and reference code for engineers. It includes code for graph algorithms, heap data structures, stacks, queues, and more — each implemented cleanly so learners can trace logic and adapt for their problems. The repository is particularly useful for people preparing for competitive programming, job interviews, or building a foundational understanding of algorithmic patterns. Because it’s openly maintained, you can browse through issues, see test cases, and observe coding style in a “learning through code” fashion. It also serves as a playground where you can add problems, measure performance, and compare different algorithmic approaches. For anyone striving to move from “I know the syntax” to “I know how to use the right algorithm at the right time,” this repository is a practical asset.

Provide implemented algorithms and functions with demo programs to test.keeped portable as possible at OS level and programming language(understanding)level.provide third party archives if available for ralvent algorithm.links for YouTube videos on availability by us and third party.

This will help a new data structure learner to learn data structures quickly.

All RL Algorithms from Scratch is an educational reinforcement learning repository built around readable Python and Jupyter Notebook implementations. Its goal is to help learners understand how major reinforcement learning algorithms work under the hood instead of hiding the logic behind large frameworks. The project includes notebooks for value-based methods, policy-gradient methods, actor-critic algorithms, model-based learning, multi-agent reinforcement learning, planning, and hierarchical approaches. Implemented topics include Q-learning, SARSA, Expected SARSA, Dyna-Q, REINFORCE, PPO, A2C, A3C, DDPG, SAC, TRPO, DQN, MADDPG, QMIX, HAC, MCTS, and PlaNet. The code prioritizes clarity, experimentation, and mathematical intuition over production speed. A companion cheat sheet gives learners a quick reference for formulas, pseudocode, and key concepts.

The Gene Expression Programming Framework in Java. It separates the process of evolution from the process of interpretation of the chromosome, allowing the use of various schemes in the chromosome.

A complete library of high-speed java collection classes to complement existing classes with new and advanced algorithms. Complements standard J2SE classes and Jakarta commons classes