Valdecy/pyCombinatorial

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Created over 3 years ago
Updated 11 months ago

Valdecy/pyCombinatorial

Valdecy

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A library to solve the TSP (Travelling Salesman Problem) using Exact Algorithms, Heuristics and Metaheuristics : 2-opt; 2.5-opt; 3-opt; 4-opt; 5-opt; 2-opt Stochastic; 2.5-opt Stochastic; 3-opt Stochastic; 4-opt Stochastic; 5-opt Stochastic; Ant Colony Optimization; Bellman-Held-Karp Exact Algorithm; Branch & Bound; BRKGA (Biased Random Key Genetic Algorithm); Brute Force; Cheapest Insertion; Christofides Algorithm; Clarke & Wright (Savings Heuristic); Concave Hull Algorithm; Convex Hull Algorithm; Elastic Net; Extremal Optimization; Farthest Insertion; Genetic Algorithm; GRASP (Greedy Randomized Adaptive Search Procedure); Greedy Karp-Steele Patching; Guided Search; Hopfield Network; Iterated Search; Karp-Steele Patching; Multifragment Heuristic; Nearest Insertion; Nearest Neighbour; Random Insertion; Random Tour; Scatter Search; Simulated Annealing; SOM (Self Organizing Maps); Space Filling Curve (Hilbert); Space Filling Curve (Morton); Space Filling Curve (Sierpinski); Stochastic Hill Climbing; Sweep; Tabu Search; Truncated Branch & Bound; Twice-Around the Tree Algorithm (Double Tree Algorithm); Variable Neighborhood Search.

pyMetaheuristic

pyMetaheuristic: A Comprehensive Python Library for Optimization

pyDecision

pyDecision is a comprehensive Python library that encompasses a wide array of Multi-Criteria Decision Analysis (MCDA) methods. These powerful and versatile tools assist in making effective decisions by comparing alternatives based on multiple criteria, making it a valuable resource for researchers, analysts, and decision-makers.

pyMultiobjective

A python library for the following Multiobjective Optimization Algorithms or Many Objectives Optimization Algorithms: C-NSGA II; CTAEA; GrEA; HypE; IBEA-FC; IBEA-HV; MOEA/D; NAEMO; NSGA II; NSGA III; OMOPSO; PAES; RVEA; SMPSO; SMS-EMOA; SPEA2; U-NSGA III

pyBibX

A Bibliometric and Scientometric Python Library Powered with Artificial Intelligence Tools

Metaheuristic-Grey_Wolf_Optimizer

Grey Wolf Optimizer to Minimize Functions with Continuous Variables

pyVRP

The pyVRP is python library that solves (using Genetic Algorithms): Capacitated VRP, Multiple Depot VRP, VRP with Time Windows, VRP with Homogeneous or Heterogeneous Fleet, VRP with Finite or Infinite Fleet, Open or Closed Routes, TSP, mTSP and various combination of these types.

pyInterDemand

A python Library for Intermittent Demand Methods: Croston, SBA, SBJ, TSB, HES, LES and SES

Metaheuristic-Local_Search-Variable_Neighborhood_Search

Variable Neighborhood Search Function for TSP problems

C4.5

C4.5 Algorithm - A Decision Tree for Numerical and Categorical Data that can Handle Missing Values and Pruning Methods

Metaheuristic-Whale_Optimization_Algorithm

Whale Optimization Algorithm to Minimize Functions with Continuous Variables

Metaheuristic-Local_Search-GRASP

GRASP (Greedy Randomized Adaptive Search Procedure) Function for TSP problems.

Metaheuristic-Salp_Swarm_Algorithm

Salp Swarm Algorithm to Minimize Functions with Continuous Variables

J-Electre

Electre I, I_s, I_v, II, III, IV, TRI and TRI-ME Software

J-Horizon

(Update-15-MAY-2020) A Vehicle Routing Problem Software. CVRP (Capacitated VRP), MDVRP (Multiple Depot VRP), VRPTW (VRP with Time Windows), VRPB (VRP with Backhauls), VRPPD (VRP with Pickups and Deliveries), VRP with Homogeneous or Heterogeneous Fleet, Finite or Infinite Fleet, TSP, mTSP and various combination of these types

Metaheuristic-Flower_Pollination_Algorithm

Flower Pollination Algorithm to Minimize Functions with Continuous Variables

Summary

Summary of my Repositories with Hyperlinks. Lessons and Colab Demos are also included. SEMENDE 2023 (AI Talk) https://bit.ly/46UwTnD

Metaheuristic-Sine_Cosine_Algorithm

Sine Cosine Algorithm to Minimize Functions with Continuous Variables

Metaheuristic-Ant_Lion_Optimizer

Ant Lion Optimizer to Minimize Functions with Continuous Variables

Metaheuristic-Artificial_Bee_Colony_Optimization

Artificial Bee Colony Optimization to Minimize Functions with Continuous Variables

Metaheuristic-SPEA_2

SPEA 2 (Strength Pareto Evolutionary Algorithm 2) Function to Minimize Multiple Objectives with Continuous Variables. Real Values Encoded

Metaheuristic-Multi-Verse_Optimizer

Multi-Verse Optimizer to Minimize Functions with Continuous Variables

Recommender-Systems-Content_Based_Filtering

Content-Based Filtering using TF-IDF Matrices with Cosine Similarity

Metaheuristic-Local_Search-Tabu_Search

Tabu Search Function for TSP problems

Datasets

Datasets used in the Google Colab Lessons

Metaheuristic-Local_Search-2-opt_Stochastic

Stochastic 2-opt Function for TSP problems

Metaheuristic-Local_Search-Scatter_Search

Scatter Search Function for TSP problems

Metaheuristic-Cuckoo_Search

Cuckoo Search to Minimize Functions with Continuous Variables

Metaheuristic-Moth_Flame_Algorithm

Moth Flame Algorithm to Minimize Functions with Continuous Variables

CART

CART Algorithm - A Decision Tree for Numerical and Categorical Data that can Handle Missing Values and Pruning Methods

pyAutoSummarizer

pyAutoSummarizer - An Extractive and Abstractive Summarization Library Powered with Artificial Intelligence

Metaheuristic-Local_Search-Extremal_Optimization

Extremal Optimization Function for TSP problems

Metaheuristic-Local-Search-3-opt

3-opt Function for TSP problems

Metaheuristic-Local_Search-Iterated_Search

Iterated Search Function for TSP problems

Forecasting-01-Moving_Averages

Calculates the Centered Moving Average (Weighted, Simple or Exponential) of a Time Series

mcdm_scheduler

A MCDM approach for Scheduling Problems

Voracious-AHP

This software remove or reduce the inconsistency from an AHP Matrix

Latent-Dirichlet-Allocation

Latent Dirichlet Allocation (LDA) function. Also computes the dtm, binary dtm, tf dtm and tf-idf dtm

Metaheuristic-Firefly_Algorithm

Firefly Algorithm to Minimize Functions with Continuous Variables

ELECTRE-Tree

Metaheuristic-Simulated_Annealing

Simulated Annealing to Minimize Functions with Continuous Variables

Metaheuristic-Ant_Colony_Optimization

Ant Colony Optimization Function for TSP problems

Ranking-Trees

Ranking-Trees Multicriteria Algorithm

pyRecommenderSystem

A Recommender System Python Library

Metaheuristic-Local-Search-2-opt

2-opt Function for TSP problems

Metaheuristic-Local_Search-Guided_Search

Guided Search Function for TSP problems

Data_Science_Models

Machine Learning, Deep Machine Learning & Artificial Intelligence Models in MS EXCEL

Metaheuristic-Local-Search-4-opt

4-opt Function for TSP problems

Random-Forest

Random Forest Algorithm - A Decision Tree Ensemble for Numerical and Categorical Data that can Handle Missing Values

Metaheuristic-Memetic_Algorithm

Memetic Algorithm with Lamarckian Learning (xhc - Crossover Hill Climbing) to Minimize Functions with Continuous Variables. Real Values Encoding

Iterative-Dichotomiser-3

ID3 Algorithm - A Decision Tree for Categorical Data with Pruning Methods

Metaheuristic-Cross_Entropy_Method

Cross Entropy Method (or Kullback–Leibler divergence) to Minimize Functions with Continuous Variables

Neural-Networks

Pure Python Neural Network Function for Binary or Linear Problems

Metaheuristic-NSGA_II

NSGA II (Non-Dominated Sorting Genetic Algorithm II) Function to Minimize Multiple Objectives with Continuous Variables. Real Values Encoded

Recommender-Systems-Collaborative_Filtering-Regression_User_Based

Collaborative Filtering Function using an User Based Regression Approach

ec_promethee

The EC-PROMETHEE Method - A Committee Approach for Outranking Problems Using Randoms Weights

pyCritical

CPM & PERT methods with Gantt chart plots

ga_scheduler

A Comprehensive Library for Solving Machine Scheduling Problems Using Genetic Algorithms

Forecasting

Metaheuristic-Bat_Algorithm

Bat Algorithm to Minimize Functions with Continuous Variables

Metaheuristic-Particle_Swarm_Optimization

Paticle Swarm Optimization to Minimize Functions with Continuous Variables

pyMissingAHP

A Method to Infer AHP Missing Pairwise Comparisons

Method_3MOAHP

Inconsistency Reduction Technique for AHP and Fuzzy-AHP Methods

Forecasting-04-Holt_Winters

Calculates the Additive or Multiplicative Holt-Winters' Method for Time Series with Trend and Seasonality

Reinforcement-Learning

Solving Games (Tic-Tac-Toe and Gridworld) using the Q-Learning Algorithm, a Tabular Reinforcement Learning Technique. Code in Python, Game in html