yyicc1108

yyicc1108's Stars

• Xi-L/PSL-MOBO

  Language:Python316

• kjappelbaum/pyepal

  Multiobjective active learning with tunable accuracy/efficiency tradeoff and clear stopping criterion.

  Language:Python375

• tamuhey/qubogen

  QUBO matrix generator for major combinatorial optimization problems written in Python

  Language:Jupyter Notebook239

• FujitsuResearch/autoqubo

  Automatic tool for converting a high-level description of an optimization problem, written in Python, into an equivalent QUBO.

  Language:Python133

• Technician13/MIT-Cheetah-Note

  MIT Cheetah仿真平台源码笔记以及一部分第三方组件

  11322

• Farama-Foundation/MO-Gymnasium

  Multi-objective Gymnasium environments for reinforcement learning

  Language:Python27636

• LucasAlegre/morl-baselines

  Multi-Objective Reinforcement Learning algorithms implementations.

  Language:Python28445

• RunzheYang/MORL

  Multi-Objective Reinforcement Learning

  Language:Python24749

• kevin031060/Genetic_Local_Search_TSP

  Language:Python105

• MOEA-NSM/moea-nsm

  Language:Java11

• emre-kocyigit/genetic_algorithm_tsp

  You can use this package for Travelling Salesman Problem-related optimization problems such as Route Planning, Delivery Management etc. I implemented all important operators of Genetic Algorithm: Crossover, Mutation, Elitism, Tournament Selection etc. I created a dataset which contains 20 points, and each point has X-Y coordinates. You can use this dataset or any dataset which is in the same form without major modifying in the code.

  Language:Python63

• jonalloub/Genetic-Algorithm-Crossover-Operators

  Comparing performance of single point crossover, two point crossover, cut and splice, uniform crossover in Generic Algorithm for 8 queens problem

  Language:Python22

• johnmath/cyclic-decomposition

  Language:Jupyter Notebook1

• ZhangNieng/Review-Status

  Language:Jupyter Notebook4

• FedUni/MORL

  Multi-Objective Reinforcement Learning components built on top of RL glue components

  Language:Java271

• garlicdevs/Fruit-API

  A Universal Deep Reinforcement Learning Framework

  Language:Python6722

• mfinzi/equivariant-MLP

  A library for programmatically generating equivariant layers through constraint solving

  Language:Jupyter Notebook25321

• GiovaniCenta/Pareto-Deep-Q-Networks

  Implementation of Pareto Deep Q Networks in a multi-objective Gym Reinforcement Learning Environment

  Language:Python91

• ElisevanderPol/marl_homomorphic_networks

  Language:Python51

• DLR-RM/stable-baselines3

  PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

  Language:Python8.9k1.7k

• NEUAI/neuthesis-enhanced

  东北大学博士、硕士学位论文模板

  Language:TeX3711

• isl-org/MultiObjectiveOptimization

  Source code for Neural Information Processing Systems (NeurIPS) 2018 paper "Multi-Task Learning as Multi-Objective Optimization"

  Language:Python978171

• median-research-group/LibMTL

  A PyTorch Library for Multi-Task Learning

  Language:Python2k183

• afcsilva/PMITS-for-QAPVar

  Contains the executable files of PMITS to solve the QAP variants

  Language:C++2

• seolhokim/InverseRL-Pytorch

  Pytorch GAIL VAIL AIRL VAIRL EAIRL SQIL Implementation

  Language:Python6110

• mit-gfx/PGMORL

  [ICML 2020] Prediction-Guided Multi-Objective Reinforcement Learning for Continuous Robot Control

  Language:Python10030

• Valdecy/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

  Language:Python15425

• CarlossShi/tsp-meta-heuristic

  Python implementation of Tabu Search (TB), Genetic Algorithm (GA), and Simulated Annealing (SA) solving Travelling Salesman Problem (TSP). Term project of Intelligent Optimization Methods, UCAS course 070105M05002H. 禁忌搜索, 遗传算法, 模拟退火解旅行商问题的Python实现. **科学院大学现代智能优化方法大作业.

  Language:Python293

• rameziophobia/Travelling_Salesman_Optimization

  Python implementation for TSP using Genetic Algorithms, Simulated Annealing, PSO (Particle Swarm Optimization), Dynamic Programming, Brute Force, Greedy and Divide and Conquer

  Language:Python7520

• marcoscastro/tsp_pso

  Solution to TSP (Travelling salesman problem) using Particle Swarm Optimization (PSO) - Language: Python

  Language:Python6538