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7 dépôts

Awesome GitHub RepositoriesTree-Based Optimization

Calculates optimal values across tree structures by performing depth-first searches to aggregate results from child nodes.

Distinct from Tree Node Templates: Focuses on DP-based tree aggregation, distinct from build-time tree-shaking.

Explore 7 awesome GitHub repositories matching software engineering & architecture · Tree-Based Optimization. Refine with filters or upvote what's useful.

Awesome Tree-Based Optimization GitHub Repositories

Trouvez les meilleurs dépôts grâce à l'IA.Nous recherchons les dépôts les plus pertinents grâce à l'IA.
  • oi-wiki/oi-wikiAvatar de OI-wiki

    OI-wiki/OI-wiki

    26,176Voir sur GitHub↗

    This project is a comprehensive, community-maintained knowledge base and toolkit designed for competitive programming. It serves as a centralized repository for algorithmic theory, data structures, and mathematical techniques, providing a structured reference for informatics and collegiate programming competitions. The project distinguishes itself by integrating educational content with a robust suite of automation utilities. It provides a complete workflow for competitive programming, including tools for automated test case generation, solution verification, and direct interaction with onlin

    Aggregates optimal values across tree structures using depth-first search techniques for dynamic programming.

    TypeScriptacm-icpcacm-icpc-handbookalgorithms
    Voir sur GitHub↗26,176
  • maaassistantarknights/maaassistantarknightsAvatar de MaaAssistantArknights

    MaaAssistantArknights/MaaAssistantArknights

    21,583Voir sur GitHub↗

    MaaAssistantArknights is a cross-platform automation engine designed for mobile games, utilizing computer vision and input simulation to perform routine tasks. It functions as an Android emulator controller, managing game lifecycles, resource farming, and infrastructure optimization through structured, scripted workflows. The project distinguishes itself through a modular configuration system that allows users to define complex automation logic via external instruction files. This framework supports dynamic task modification, configuration inheritance, and schema validation, ensuring that cus

    Calculates optimal operator assignments to facilities to maximize resource production.

    C++arknightscomputer-visionmaa
    Voir sur GitHub↗21,583
  • sharingsource/logicstack-leetcodeAvatar de SharingSource

    SharingSource/LogicStack-LeetCode

    7,495Voir sur GitHub↗

    LogicStack-LeetCode is a curated repository of solved algorithm problems and data structure implementations, primarily drawn from the LeetCode platform. Its core identity is a structured collection of solutions designed to support technical interview preparation and competitive programming practice, with each solution accompanied by complexity analyses to help engineers understand performance trade-offs. The repository distinguishes itself through its breadth of coverage across fundamental algorithmic patterns and data structures. It includes implementations for array manipulation, string pro

    Solves the longest path problem in trees with distinct adjacent character constraints.

    algorithminterview-practiceinterview-questions
    Voir sur GitHub↗7,495
  • deap/deapAvatar de DEAP

    DEAP/deap

    6,336Voir sur GitHub↗

    Represents programs as nested tree structures with typed nodes for genetic programming operations.

    Python
    Voir sur GitHub↗6,336
  • algorithmicsuperintelligence/openevolveAvatar de algorithmicsuperintelligence

    algorithmicsuperintelligence/openevolve

    5,421Voir sur GitHub↗

    OpenEvolve is an open-source framework for evolutionary computation that uses language models to drive automated optimization across multiple domains. It can evolve system prompts for large language models, refine source code across programming languages, search for optimal GPU kernel configurations, discover interpretable mathematical expressions from data, and maintain diverse populations of high-performing solutions. The framework integrates multiple evolutionary strategies, including MAP-Elites diversity mapping and island-based topologies, to avoid premature convergence and preserve a wid

    Evo evolves a program that passes all test cases on an online judge by iteratively mutating and selecting candidate solutions.

    Pythonalpha-evolvealphacodealphaevolve
    Voir sur GitHub↗5,421
  • chrxh/alienAvatar de chrxh

    chrxh/alien

    5,354Voir sur GitHub↗

    Evolve is an evolution-based organism designer and GPU-accelerated artificial life simulator that combines interactive particle physics with a real-time simulation editor. At its core, it runs genetic algorithm evolution on self-replicating graph structures to evolve digital organisms, offloading particle physics, neural networks, and rendering entirely to the GPU through a compute shader pipeline for real-time performance. The project distinguishes itself with graph-based organism design that uses a directed graph editor to visually define organism structure, connections, and neural controll

    Evolves digital organisms with neural networks and genetic algorithms to develop complex behaviors without manual programming.

    C++agent-based-simulationartificial-lifecuda
    Voir sur GitHub↗5,354
  • soapyigu/leetcode-swiftAvatar de soapyigu

    soapyigu/LeetCode-Swift

    4,958Voir sur GitHub↗

    LeetCode-Swift is a collection of algorithm solutions written in Swift, designed for coding interview preparation. Each solution is implemented as a self-contained function with no external dependencies, making it easy to run and test. The repository organizes solutions by topic and company, and every file includes time and space complexity annotations, allowing quick evaluation of algorithmic efficiency. What sets this repository apart is its flat file structure and the way solutions are tagged with the companies that asked them in interviews, enabling targeted practice. All code resides in

    Computes optimal solutions on binary trees with adjacency constraints using recursion and two-state DP.

    Swiftalgorithmdata-structuresinterview
    Voir sur GitHub↗4,958
  1. Home
  2. Software Engineering & Architecture
  3. Trees
  4. Tree Node Templates
  5. Tree-Based Optimization

Explorer les sous-tags

  • Adjacency-Constrained Tree DP1 sous-tagRecursive algorithms that compute optimal values on binary trees with adjacency constraints using two-state tracking. **Distinct from Tree-Based Optimization:** Distinct from Tree-Based Optimization: specifically handles adjacency constraints (e.g., cannot pick adjacent nodes).
  • Genetic Program Evolution1 sous-tagRepresents solutions as tree structures and applies crossover, mutation, and selection to evolve them over generations. **Distinct from Tree-Based Optimization:** Distinct from general Tree-Based Optimization: specifically for evolving programs via genetic operators, not for DP-based tree aggregation.
  • Genetic Program TreesRepresents programs as nested tree structures with typed nodes for crossover and mutation on symbolic expressions. **Distinct from Tree-Based Optimization:** Distinct from general Tree-Based Optimization: specifically for representing and evolving programs, not for DP-based tree aggregation.