{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/learning-to-dispatch-for-job-shop-scheduling","title":"Learning to Dispatch for Job Shop Scheduling via Deep Reinforcement Learning","arxiv_id":"2010.12367","date":"2020-10-23","proceeding":"NeurIPS 2020 12","authors":["Cong Zhang","Wen Song","Zhiguang Cao","Jie Zhang","Puay Siew Tan","Chi Xu"],"abstract":"Priority dispatching rule (PDR) is widely used for solving real-world Job-shop scheduling problem (JSSP). However, the design of effective PDRs is a tedious task, requiring a myriad of specialized knowledge and often delivering limited performance. In this paper, we propose to automatically learn PDRs via an end-to-end deep reinforcement learning agent. We exploit the disjunctive graph representation of JSSP, and propose a Graph Neural Network based scheme to embed the states encountered during solving. The resulting policy network is size-agnostic, effectively enabling generalization on large-scale instances. Experiments show that the agent can learn high-quality PDRs from scratch with elementary raw features, and demonstrates strong performance against the best existing PDRs. The learned policies also perform well on much larger instances that are unseen in training.","url_abs":"https://arxiv.org/abs/2010.12367v1","url_pdf":"https://arxiv.org/pdf/2010.12367v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"learning-to-dispatch-for-job-shop-scheduling","repo_url":"https://github.com/zcajiayin/L2D","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"learning-to-dispatch-for-job-shop-scheduling","repo_url":"https://github.com/MattJud/gnn_jssp","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"learning-to-dispatch-for-job-shop-scheduling","repo_url":"https://github.com/jolibrain/wheatley","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"NOASSERTION"}},{"paper_slug":"learning-to-dispatch-for-job-shop-scheduling","repo_url":"https://github.com/tmdt-buw/schlably","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"Apache-2.0"}}],"tasks":[{"task_slug":"deep-reinforcement-learning","task_name":"Deep Reinforcement Learning"},{"task_slug":"graph-neural-network","task_name":"Graph Neural Network"},{"task_slug":"job-shop-scheduling","task_name":"Job Shop Scheduling"},{"task_slug":"reinforcement-learning-1","task_name":"Reinforcement Learning (RL)"},{"task_slug":"scheduling","task_name":"Scheduling"},{"task_slug":"reinforcement-learning-2","task_name":"reinforcement-learning"}],"methods":[{"method_slug":"graph-neural-network","method_name":"Graph Neural Network"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=2010.12367","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2010.12367"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/zcajiayin/L2D","reach":{"status":"ok"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/tmdt-buw/schlably","reach":{"status":"ok","spdx":"Apache-2.0"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/MattJud/gnn_jssp","reach":{"status":"ok"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/jolibrain/wheatley","reach":{"status":"ok","spdx":"NOASSERTION"}}],"summary":{"unverified":3},"by_repo_kind":{"listed":{"samples":3,"ran":0,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":0,"samples":[{"code_sha256_prefix":"6858af4a494f0e3c","entry":"complete_config","repo":"tmdt-buw/schlably","repo_kind":"listed","path":"src/agents/train_test_utility_functions.py","file_url":"https://github.com/tmdt-buw/schlably/blob/HEAD/src/agents/train_test_utility_functions.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"6858af4a494f0e3c"}},{"code_sha256_prefix":"7dde7f433f1684bc","entry":"load","repo":"tmdt-buw/schlably","repo_kind":"listed","path":"src/agents/rllib_interface.py","file_url":"https://github.com/tmdt-buw/schlably/blob/HEAD/src/agents/rllib_interface.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"7dde7f433f1684bc"}},{"code_sha256_prefix":"e6a2b897802472fb","entry":"timing_decorator_factory","repo":"tmdt-buw/schlably","repo_kind":"listed","path":"src/code_tests/timer.py","file_url":"https://github.com/tmdt-buw/schlably/blob/HEAD/src/code_tests/timer.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"e6a2b897802472fb"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}