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alphatree-graphic-deep-neural-network

AI Roadmap:机器学习(Machine Learning)、深度学习(Deep Learning)、对抗神经网络(GAN），图神经网络（GNN），NLP，大数据相关的发展路书(roadmap), 并附海量源码（python，pytorch）带大家消化基本知识点，突破面试，完成从新手到合格工程师的跨越，其中深度学习相关论文附有tensorflow caffe官方源码，应用部分含推荐算法和知识图谱

automation-of-a-production-line

Automating the production of a flexible production line simulator, development of a MES (Manufacturing Execution System) to monitor and manage the production on the plant floor and development of an ERP (Enterprise Resource Planning) module to receive orders from clients and schedule acquisition orders as well as production orders.

bitmesclient

it is BitMES Client

ddqn_fjsp

deep-reinforcement-learning-algorithms-with-pytorch

PyTorch implementations of deep reinforcement learning algorithms and environments

deep_reinforcement_learning_fjsp

dfjsp

重调度

dive-into-dl-pytorch

本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。

djsp

DRL for DJSP

docplex-examples

These samples demonstrate how to use the DOcplex library to model and solve optimization problems.

dqn-fjsp

代码学习使用

drl4djsp

DRL for solving the dynamic job shop schedule problems with uncertain time

etdqn

Evolutionary Trainer-based Deep Q-Network for Dynamic Flexible Job Shop Scheduling

fjsp

cplex for FJSP

fjsp-gnnrl

Solving Flexible Job Shop Scheduling by learning to dispatch with Deep Reinforcement Learning

fjsp-rl

fjspdrl

The code and data will be published after accepting our paper

fjspt

Result files and instances for Flexible Job-Shop Scheduling Problem with Transportation resources

job-shop-scheduling-problem-javascript

Reactjs application with Web workers to demonstrate how to optimize a Job Shop Scheduling Problem with javascript without using any libraries.

job_shop_scheduling_benchmark_environments_and_instances

A benchmarking repo with various solution methods to various machine scheduling problems

jobshopplannerdemo

Job Shop Scheduling Demo using JS React as front end and Python as optimiser/backend

mfjsp

This is a rep for nsga-iii solve many objective flexible job shop schedule problem

mhgnn_fjsp

morl

Multi-Objective Reinforcement Learning

multi-agent-deep-deterministic-policy-gradients

A Pytorch implementation of the multi agent deep deterministic policy gradients (MADDPG) algorithm

pygat

Pytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)

python-lekin

python-lekin: Flexible supply chain planning and scheduler in Python

rl-hh

强化学习超启发式算法求解 FJSP 问题个人毕设

rl-jsp

Deep Reinforcement Learning Based on Graph Neural Networks for Job-shop Scheduling

rl_for_dynamic_scheduling

Implementation of the paper "A Reinforcement Learning Based Strategy for Dynamic Scheduling on Heterogeneous Platforms".