{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:DGP5VF3L5PQGZBSZBZSKEMK74P","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"72c9a71966658e408ea9d310fe4824920884075f07982048f07ed7d5c69ab598","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2024-06-20T08:22:07Z","title_canon_sha256":"44c16c4659d019af78265c28a0d5c692b415e4a1ba69bdc487ce1f9301070591"},"schema_version":"1.0","source":{"id":"2406.14096","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.14096","created_at":"2026-07-05T09:45:11Z"},{"alias_kind":"arxiv_version","alias_value":"2406.14096v3","created_at":"2026-07-05T09:45:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.14096","created_at":"2026-07-05T09:45:11Z"},{"alias_kind":"pith_short_12","alias_value":"DGP5VF3L5PQG","created_at":"2026-07-05T09:45:11Z"},{"alias_kind":"pith_short_16","alias_value":"DGP5VF3L5PQGZBSZ","created_at":"2026-07-05T09:45:11Z"},{"alias_kind":"pith_short_8","alias_value":"DGP5VF3L","created_at":"2026-07-05T09:45:11Z"}],"graph_snapshots":[{"event_id":"sha256:c3475770fe89c50b9068fe41f8c99d14654e711f58835c82ac8fce4c2c930d0f","target":"graph","created_at":"2026-07-05T09:45:11Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2406.14096/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Job shop scheduling problems (JSSPs) represent a critical and challenging class of combinatorial optimization problems. Recent years have witnessed a rapid increase in the application of graph neural networks (GNNs) to solve JSSPs, albeit lacking a systematic survey of the relevant literature. This paper aims to thoroughly review prevailing GNN methods for different types of JSSPs and the closely related flow-shop scheduling problems (FSPs), especially those leveraging deep reinforcement learning (DRL). We begin by presenting the graph representations of various JSSPs, followed by an introduct","authors_text":"Cong Zhang, Igor G. Smit, Jianan Zhou, Jian Chen, Robbert Reijnen, Wim Nuijten, Yaoxin Wu, Yingqian Zhang, Zaharah Bukhsh","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2024-06-20T08:22:07Z","title":"Graph Neural Networks for Job Shop Scheduling Problems: A Survey"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.14096","kind":"arxiv","version":3},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:35725c500e2d1f321b8374ff2d6c4633ce6a0f2f6ba33b23da5d9ee3d7d8eaa5","target":"record","created_at":"2026-07-05T09:45:11Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"72c9a71966658e408ea9d310fe4824920884075f07982048f07ed7d5c69ab598","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2024-06-20T08:22:07Z","title_canon_sha256":"44c16c4659d019af78265c28a0d5c692b415e4a1ba69bdc487ce1f9301070591"},"schema_version":"1.0","source":{"id":"2406.14096","kind":"arxiv","version":3}},"canonical_sha256":"199fda976bebe06c86590e64a2315fe3eeccc6af39ec43bc55004aee4b2a3dee","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"199fda976bebe06c86590e64a2315fe3eeccc6af39ec43bc55004aee4b2a3dee","first_computed_at":"2026-07-05T09:45:11.017395Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:45:11.017395Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"uCx1MrdoBXX3jXijCqba6DFZwLxZWBjsHJlWElwRvBT0qJ9koYv+oYyNu2A43A4+94U/Ph6vigyWjjWmAqpzAA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:45:11.017886Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.14096","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:35725c500e2d1f321b8374ff2d6c4633ce6a0f2f6ba33b23da5d9ee3d7d8eaa5","sha256:c3475770fe89c50b9068fe41f8c99d14654e711f58835c82ac8fce4c2c930d0f"],"state_sha256":"bdbe80e3b1330f6c1717a4611ecde46bab631ca3096ab19a4b38fda4b6ff234c"}