{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:1996:R4FO5EBBCCDWN4IA27MO6BVN2M","short_pith_number":"pith:R4FO5EBB","schema_version":"1.0","canonical_sha256":"8f0aee9021108766f100d7d8ef06add32b3c16374dbd05839208fa62d1e42fc6","source":{"kind":"arxiv","id":"cond-mat/9605071","version":1},"attestation_state":"computed","paper":{"title":"Airline Crew Scheduling with Potts Neurons","license":"","headline":"","cross_cats":["hep-lat"],"primary_cat":"cond-mat","authors_text":"B. S\\\"oderberg (Theoretical Physics, C. Peterson, Lund U.), M. Lagerholm","submitted_at":"1996-05-11T09:04:43Z","abstract_excerpt":"A Potts feedback neural network approach for finding good solutions to resource allocation problems with a non-fixed topology is presented. As a target application the airline crew scheduling problem is chosen. The topological complication is handled by means of a propagator defined in terms of Potts neurons. The approach is tested on artificial random problems tuned to resemble real-world conditions. Very good results are obtained for a variety of problem sizes. The computer time demand for the approach only grows like $\\mbox{(number of flights)}^3$. A realistic problem typically is solved wi"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"cond-mat/9605071","kind":"arxiv","version":1},"metadata":{"license":"","primary_cat":"cond-mat","submitted_at":"1996-05-11T09:04:43Z","cross_cats_sorted":["hep-lat"],"title_canon_sha256":"2321e62552da4cef4c54fa26fdcce398ea74739807d66c9a91c6398a546e5dc6","abstract_canon_sha256":"7404bf8bbf290070d85891a6735d81e9d685534c575a02814e3f507b1b784a2d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:09:20.431460Z","signature_b64":"KiA7xz6HXmLXbI5tiJ3WyAuwq0z/eUYjqufe0TbjLSJLf3N7esIRfmFds8HQ5jxdhtn+TiETSnqeSk00BdbpBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8f0aee9021108766f100d7d8ef06add32b3c16374dbd05839208fa62d1e42fc6","last_reissued_at":"2026-05-18T01:09:20.431021Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:09:20.431021Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Airline Crew Scheduling with Potts Neurons","license":"","headline":"","cross_cats":["hep-lat"],"primary_cat":"cond-mat","authors_text":"B. S\\\"oderberg (Theoretical Physics, C. Peterson, Lund U.), M. Lagerholm","submitted_at":"1996-05-11T09:04:43Z","abstract_excerpt":"A Potts feedback neural network approach for finding good solutions to resource allocation problems with a non-fixed topology is presented. As a target application the airline crew scheduling problem is chosen. The topological complication is handled by means of a propagator defined in terms of Potts neurons. The approach is tested on artificial random problems tuned to resemble real-world conditions. Very good results are obtained for a variety of problem sizes. The computer time demand for the approach only grows like $\\mbox{(number of flights)}^3$. A realistic problem typically is solved wi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"cond-mat/9605071","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"cond-mat/9605071","created_at":"2026-05-18T01:09:20.431093+00:00"},{"alias_kind":"arxiv_version","alias_value":"cond-mat/9605071v1","created_at":"2026-05-18T01:09:20.431093+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.cond-mat/9605071","created_at":"2026-05-18T01:09:20.431093+00:00"},{"alias_kind":"pith_short_12","alias_value":"R4FO5EBBCCDW","created_at":"2026-05-18T12:25:48.327863+00:00"},{"alias_kind":"pith_short_16","alias_value":"R4FO5EBBCCDWN4IA","created_at":"2026-05-18T12:25:48.327863+00:00"},{"alias_kind":"pith_short_8","alias_value":"R4FO5EBB","created_at":"2026-05-18T12:25:48.327863+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/R4FO5EBBCCDWN4IA27MO6BVN2M","json":"https://pith.science/pith/R4FO5EBBCCDWN4IA27MO6BVN2M.json","graph_json":"https://pith.science/api/pith-number/R4FO5EBBCCDWN4IA27MO6BVN2M/graph.json","events_json":"https://pith.science/api/pith-number/R4FO5EBBCCDWN4IA27MO6BVN2M/events.json","paper":"https://pith.science/paper/R4FO5EBB"},"agent_actions":{"view_html":"https://pith.science/pith/R4FO5EBBCCDWN4IA27MO6BVN2M","download_json":"https://pith.science/pith/R4FO5EBBCCDWN4IA27MO6BVN2M.json","view_paper":"https://pith.science/paper/R4FO5EBB","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=cond-mat/9605071&json=true","fetch_graph":"https://pith.science/api/pith-number/R4FO5EBBCCDWN4IA27MO6BVN2M/graph.json","fetch_events":"https://pith.science/api/pith-number/R4FO5EBBCCDWN4IA27MO6BVN2M/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/R4FO5EBBCCDWN4IA27MO6BVN2M/action/timestamp_anchor","attest_storage":"https://pith.science/pith/R4FO5EBBCCDWN4IA27MO6BVN2M/action/storage_attestation","attest_author":"https://pith.science/pith/R4FO5EBBCCDWN4IA27MO6BVN2M/action/author_attestation","sign_citation":"https://pith.science/pith/R4FO5EBBCCDWN4IA27MO6BVN2M/action/citation_signature","submit_replication":"https://pith.science/pith/R4FO5EBBCCDWN4IA27MO6BVN2M/action/replication_record"}},"created_at":"2026-05-18T01:09:20.431093+00:00","updated_at":"2026-05-18T01:09:20.431093+00:00"}