PGRL

This repository is the official PyTorch implementation of the algorithms of the paper: Fast Pareto Set Approximation for Multi-Objective Flexible Job Shop Scheduling via Parallel Preference-Conditioned Graph Reinforcement Learning

Installation

torch 1.8.1

python 3.8.15

gym 0.18.0

numpy 1.24.1

Name		Name	Last commit message	Last commit date
Latest commit History 9 Commits
.idea		.idea
FJSP-benchmarks		FJSP-benchmarks
multi_opt_models		multi_opt_models
saved_network_MOFJSP/3_obj		saved_network_MOFJSP/3_obj
utils		utils
ES_parallel_training.py		ES_parallel_training.py
ES_parallel_training2.py		ES_parallel_training2.py
ES_train_origin.py		ES_train_origin.py
FJSP_Env.py		FJSP_Env.py
PGRL-10x10.csv		PGRL-10x10.csv
PGRL-15x15.csv		PGRL-15x15.csv
PGRL-20x20.csv		PGRL-20x20.csv
PGRL-30x20.csv		PGRL-30x20.csv
PGRL-40x20.csv		PGRL-40x20.csv
PGRL-50x20.csv		PGRL-50x20.csv
PGRL-6x6.csv		PGRL-6x6.csv
Params.py		Params.py
README.md		README.md
mb_agg.py		mb_agg.py
mo_utils.py		mo_utils.py
policy.py		policy.py
test_benchmark.py		test_benchmark.py
test_gen_ins.py		test_gen_ins.py
uniform_instance.py		uniform_instance.py
validation_optimization_3_obj.py		validation_optimization_3_obj.py

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