Job Shop Scheduling

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Most implemented papers archive 2025-07-28

30 shown of 35 papers with code (92 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• A Reinforcement Learning Environment For Job-Shop Scheduling
  8 Apr 2021 4 repositories listed
  Scheduling is a fundamental task occurring in various automated systems applications, e.
• Learning to Dispatch for Job Shop Scheduling via Deep Reinforcement Learning
  23 Oct 2020 4 repositories listed Syntology ran 0 of 3 samples · 3 unverified
  Priority dispatching rule (PDR) is widely used for solving real-world Job-shop scheduling problem (JSSP).
• Boosting Binary Optimization via Binary Classification: A Case Study of Job Shop Scheduling
  31 Aug 2018 2 repositories listed
  Many optimization techniques evaluate solutions consecutively, where the next candidate for evaluation is determined by the results of previous evaluations.
• A Production Scheduling Framework for Reinforcement Learning Under Real-World Constraints
  16 Jun 2025 1 repository listed
  The classical Job Shop Scheduling Problem (JSSP) focuses on optimizing makespan under deterministic constraints.
• Solving the Job Shop Scheduling Problem with Graph Neural Networks: A Customizable Reinforcement Learning Environment
  10 Jun 2025 1 repository listed
  This work introduces JobShopLib, a modular library that allows customizing these factors and creating new components with its reinforcement learning environment.
• Unraveling the Rainbow: can value-based methods schedule?
  6 May 2025 1 repository listed
  In this work, we conduct a comprehensive empirical evaluation of value-based algorithms, including the deep q-network and several of its advanced extensions, within the context of two complex combinatorial problems: the…
• Starjob: Dataset for LLM-Driven Job Shop Scheduling
  26 Feb 2025 1 repository listed
  Large Language Models (LLMs) have shown remarkable capabilities across various domains, but their potential for solving combinatorial optimization problems remains largely unexplored.
• Learning-Guided Rolling Horizon Optimization for Long-Horizon Flexible Job-Shop Scheduling
  18 Feb 2025 1 repository listed Syntology ran 4 of 4 samples · 0 unverified · 4 pointer-only (licence)
  Long-horizon combinatorial optimization problems (COPs), such as the Flexible Job-Shop Scheduling Problem (FJSP), often involve complex, interdependent decisions over extended time frames, posing significant challenges…
• Neural Combinatorial Optimization for Stochastic Flexible Job Shop Scheduling Problems
  18 Dec 2024 1 repository listed
  In this paper, we propose a novel attention-based scenario processing module (SPM) to extend NCO methods for solving stochastic JSPs.
• Offline Reinforcement Learning for Learning to Dispatch for Job Shop Scheduling
  16 Sep 2024 1 repository listed
  The Job Shop Scheduling Problem (JSSP) is a complex combinatorial optimization problem.
• LLMs can Schedule
  13 Aug 2024 1 repository listed Syntology ran 6 of 7 samples · 1 unverified · 7 pointer-only (licence)
  The job shop scheduling problem (JSSP) remains a significant hurdle in optimizing production processes.
• Take a Step and Reconsider: Sequence Decoding for Self-Improved Neural Combinatorial Optimization
  24 Jul 2024 1 repository listed
  The constructive approach within Neural Combinatorial Optimization (NCO) treats a combinatorial optimization problem as a finite Markov decision process, where solutions are built incrementally through a sequence of…
• Self-Improvement for Neural Combinatorial Optimization: Sample without Replacement, but Improvement
  22 Mar 2024 1 repository listed Syntology ran 0 of 5 samples · 5 unverified
  Current methods for end-to-end constructive neural combinatorial optimization usually train a policy using behavior cloning from expert solutions or policy gradient methods from reinforcement learning.
• Learning to Solve Job Shop Scheduling under Uncertainty
  4 Mar 2024 1 repository listed
  Key contributions of this research include: (1) advancements in DRL applications to JSSPs, enhancing generalization and scalability, (2) a novel method for addressing JSSPs with uncertain durations.
• Learning Topological Representations with Bidirectional Graph Attention Network for Solving Job Shop Scheduling Problem
  27 Feb 2024 1 repository listed
  Existing learning-based methods for solving job shop scheduling problems (JSSP) usually use off-the-shelf GNN models tailored to undirected graphs and neglect the rich and meaningful topological structures of…
• Self-Labeling the Job Shop Scheduling Problem
  22 Jan 2024 1 repository listed Syntology ran 0 of 2 samples · 2 unverified · 2 pointer-only (licence)
  Inspired by semi- and self-supervised learning, we show that generative models can be trained by sampling multiple solutions and using the best one according to the problem objective as a pseudo-label.
• Combinatorial Optimization with Policy Adaptation using Latent Space Search
  13 Nov 2023 1 repository listed Syntology ran 5 of 7 samples · 2 unverified · 7 pointer-only (licence)
  Combinatorial Optimization underpins many real-world applications and yet, designing performant algorithms to solve these complex, typically NP-hard, problems remains a significant research challenge.
• Job Shop Scheduling Benchmark: Environments and Instances for Learning and Non-learning Methods
  24 Aug 2023 1 repository listed Syntology ran 2 of 3 samples · 1 unverified
  We introduce an open-source GitHub repository containing comprehensive benchmarks for a wide range of machine scheduling problems, including Job Shop Scheduling (JSP), Flow Shop Scheduling (FSP), Flexible Job Shop…
• Job Shop Scheduling via Deep Reinforcement Learning: a Sequence to Sequence approach
  3 Aug 2023 1 repository listed
  We applied and tested our method in particular to some benchmark instances of Job Shop Problem, but this technique is general enough to be potentially used to tackle other different optimal job scheduling tasks with…
• An End-to-End Reinforcement Learning Approach for Job-Shop Scheduling Problems Based on Constraint Programming
  9 Jun 2023 1 repository listed Syntology ran 0 of 4 samples · 4 unverified
  Constraint Programming (CP) is a declarative programming paradigm that allows for modeling and solving combinatorial optimization problems, such as the Job-Shop Scheduling Problem (JSSP).
• Policy-Based Self-Competition for Planning Problems
  7 Jun 2023 1 repository listed
  AlphaZero-type algorithms may stop improving on single-player tasks in case the value network guiding the tree search is unable to approximate the outcome of an episode sufficiently well.
• Flexible Job Shop Scheduling via Dual Attention Network Based Reinforcement Learning
  9 May 2023 1 repository listed
  The complex relationships between operations and machines are represented precisely and concisely, for which a dual-attention network (DAN) comprising several interconnected operation message attention blocks and…
• Addressing distributional shifts in operations management: The case of order fulfillment in customized production
  24 Apr 2023 1 repository listed
  We empirically validate our proposed approach using real-world data from a job shop production that supplies large metal components to an oil platform construction yard.
• schlably: A Python Framework for Deep Reinforcement Learning Based Scheduling Experiments
  10 Jan 2023 1 repository listed
  Research on deep reinforcement learning (DRL) based production scheduling (PS) has gained a lot of attention in recent years, primarily due to the high demand for optimizing scheduling problems in diverse industry…
• Deep Reinforcement Learning Guided Improvement Heuristic for Job Shop Scheduling
  20 Nov 2022 1 repository listed
  Recent studies in using deep reinforcement learning (DRL) to solve Job-shop scheduling problems (JSSP) focus on construction heuristics.
• Winner Takes It All: Training Performant RL Populations for Combinatorial Optimization
  7 Oct 2022 1 repository listed Syntology ran 0 of 8 samples · 8 unverified
  Applying reinforcement learning (RL) to combinatorial optimization problems is attractive as it removes the need for expert knowledge or pre-solved instances.
• Learning to generalize Dispatching rules on the Job Shop Scheduling
  9 Jun 2022 1 repository listed
  Current models on the JSP do not focus on generalization, although, as we show in this work, this is key to learning better heuristics on the problem.
• Decomposition Strategies and Multi-shot ASP Solving for Job-shop Scheduling
  16 May 2022 1 repository listed
  We devise and investigate a variety of decomposition strategies in terms of the number and size of time windows as well as heuristics for choosing their operations.
• Hybrid intelligence for dynamic job-shop scheduling with deep reinforcement learning and attention mechanism
  3 Jan 2022 1 repository listed
  The dynamic job-shop scheduling problem (DJSP) is a class of scheduling tasks that specifically consider the inherent uncertainties such as changing order requirements and possible machine breakdown in realistic smart…
• An actor-critic algorithm with policy gradients to solve the job shop scheduling problem using deep double recurrent agents
  18 Oct 2021 1 repository listed
  The aim is to build up a greedy-like heuristic able to learn on some distribution of JSSP instances, different in the number of jobs and machines.

Syntology lines on 9 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.