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Job Shop Scheduling
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Scheduling Task
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Solving the Job Shop Scheduling Problem with Graph Neural Networks: A Customizable Reinforcement Learning Environment
REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models
ALAS: A Stateful Multi-LLM Agent Framework for Disruption-Aware Planning
Adaptive Bias Generalized Rollout Policy Adaptation on the Flexible Job-Shop Scheduling Problem
Unraveling the Rainbow: can value-based methods schedule?
Neural Combinatorial Optimization via Preference Optimization
Discrete Differential Evolution Particle Swarm Optimization Algorithm for Energy Saving Flexible Job Shop Scheduling Problem Considering Machine Multi States
Starjob: Dataset for LLM-Driven Job Shop Scheduling
Learning-Guided Rolling Horizon Optimization for Long-Horizon Flexible Job-Shop Scheduling
Self-Evaluation for Job-Shop Scheduling
Investigating the Monte-Carlo Tree Search Approach for the Job Shop Scheduling Problem
A Benchmarking Environment for Worker Flexibility in Flexible Job Shop Scheduling Problems
Neural Combinatorial Optimization for Stochastic Flexible Job Shop Scheduling Problems
Automatic programming via large language models with population self-evolution for dynamic job shop scheduling problem
Offline reinforcement learning for job-shop scheduling problems
A Flexible Job Shop Scheduling Problem Involving Reconfigurable Machine Tools Under Industry 5.0
A History-Guided Regional Partitioning Evolutionary Optimization for Solving the Flexible Job Shop Problem with Limited Multi-load Automated Guided Vehicles
Optimizing Job Shop Scheduling in the Furniture Industry: A Reinforcement Learning Approach Considering Machine Setup, Batch Variability, and Intralogistics
Offline Reinforcement Learning for Learning to Dispatch for Job Shop Scheduling
Developing an Algorithm Selector for Green Configuration in Scheduling Problems
Decision Transformer for Enhancing Neural Local Search on the Job Shop Scheduling Problem
LLMs can Schedule
Take a Step and Reconsider: Sequence Decoding for Self-Improved Neural Combinatorial Optimization
Graph Neural Networks for Job Shop Scheduling Problems: A Survey
Beyond Training: Optimizing Reinforcement Learning Based Job Shop Scheduling Through Adaptive Action Sampling
Multi-Representation Genetic Programming: A Case Study on Tree-based and Linear Representations
Self-Improvement for Neural Combinatorial Optimization: Sample without Replacement, but Improvement
Leveraging Constraint Programming in a Deep Learning Approach for Dynamically Solving the Flexible Job-Shop Scheduling Problem
Learning to Solve Job Shop Scheduling under Uncertainty
Learning Topological Representations with Bidirectional Graph Attention Network for Solving Job Shop Scheduling Problem
Learning-enabled Flexible Job-shop Scheduling for Scalable Smart Manufacturing
Attention-based Reinforcement Learning for Combinatorial Optimization: Application to Job Shop Scheduling Problem
Introducing PetriRL: An Innovative Framework for JSSP Resolution Integrating Petri nets and Event-based Reinforcement Learning
Self-Labeling the Job Shop Scheduling Problem
Combinatorial Optimization with Policy Adaptation using Latent Space Search
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.