{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:I4FKBSVDPDHK3K3YT6SBW2TLRR","short_pith_number":"pith:I4FKBSVD","schema_version":"1.0","canonical_sha256":"470aa0caa378ceadab789fa41b6a6b8c58efeeffff7867abf9c8899b8077c85a","source":{"kind":"arxiv","id":"1903.01885","version":1},"attestation_state":"computed","paper":{"title":"Evolutionary framework for two-stage stochastic resource allocation problems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.NE","authors_text":"Evandro C. Bracht, F\\'abio L. Usberti, M\\'ario C. San Felice, Pedro H. D. B. Hokama","submitted_at":"2018-11-29T17:30:38Z","abstract_excerpt":"Resource allocation problems are a family of problems in which resources must be selected to satisfy given demands. This paper focuses on the two-stage stochastic generalization of resource allocation problems where future demands are expressed in a finite number of possible scenarios. The goal is to select cost effective resources to be acquired in the present time (first stage), and to implement a complete solution for each scenario (second stage), while minimizing the total expected cost of the choices in both stages.\n  We propose an evolutionary framework for solving general two-stage stoc"},"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":"1903.01885","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2018-11-29T17:30:38Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"4b794ae93cc0e59b7fcaf011c57747a5bdec20d7cf7074bc10b5126ccfdaf5e8","abstract_canon_sha256":"9ce7fa40df91ef80777e636a819e57c33c42d8eb72bd35a4fbcd6ec536a51e8b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:51:59.508335Z","signature_b64":"gXpx5F5YjClbREc/m/E86aHh2Kfda9VjPeqEHUrQA8LR2syXkC+zvCXZD8YNqnfew/MEQJ9+3BLg/HVCS+dlDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"470aa0caa378ceadab789fa41b6a6b8c58efeeffff7867abf9c8899b8077c85a","last_reissued_at":"2026-05-17T23:51:59.507853Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:51:59.507853Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Evolutionary framework for two-stage stochastic resource allocation problems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.NE","authors_text":"Evandro C. Bracht, F\\'abio L. Usberti, M\\'ario C. San Felice, Pedro H. D. B. Hokama","submitted_at":"2018-11-29T17:30:38Z","abstract_excerpt":"Resource allocation problems are a family of problems in which resources must be selected to satisfy given demands. This paper focuses on the two-stage stochastic generalization of resource allocation problems where future demands are expressed in a finite number of possible scenarios. The goal is to select cost effective resources to be acquired in the present time (first stage), and to implement a complete solution for each scenario (second stage), while minimizing the total expected cost of the choices in both stages.\n  We propose an evolutionary framework for solving general two-stage stoc"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1903.01885","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":"1903.01885","created_at":"2026-05-17T23:51:59.507936+00:00"},{"alias_kind":"arxiv_version","alias_value":"1903.01885v1","created_at":"2026-05-17T23:51:59.507936+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1903.01885","created_at":"2026-05-17T23:51:59.507936+00:00"},{"alias_kind":"pith_short_12","alias_value":"I4FKBSVDPDHK","created_at":"2026-05-18T12:32:28.185984+00:00"},{"alias_kind":"pith_short_16","alias_value":"I4FKBSVDPDHK3K3Y","created_at":"2026-05-18T12:32:28.185984+00:00"},{"alias_kind":"pith_short_8","alias_value":"I4FKBSVD","created_at":"2026-05-18T12:32:28.185984+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/I4FKBSVDPDHK3K3YT6SBW2TLRR","json":"https://pith.science/pith/I4FKBSVDPDHK3K3YT6SBW2TLRR.json","graph_json":"https://pith.science/api/pith-number/I4FKBSVDPDHK3K3YT6SBW2TLRR/graph.json","events_json":"https://pith.science/api/pith-number/I4FKBSVDPDHK3K3YT6SBW2TLRR/events.json","paper":"https://pith.science/paper/I4FKBSVD"},"agent_actions":{"view_html":"https://pith.science/pith/I4FKBSVDPDHK3K3YT6SBW2TLRR","download_json":"https://pith.science/pith/I4FKBSVDPDHK3K3YT6SBW2TLRR.json","view_paper":"https://pith.science/paper/I4FKBSVD","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1903.01885&json=true","fetch_graph":"https://pith.science/api/pith-number/I4FKBSVDPDHK3K3YT6SBW2TLRR/graph.json","fetch_events":"https://pith.science/api/pith-number/I4FKBSVDPDHK3K3YT6SBW2TLRR/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/I4FKBSVDPDHK3K3YT6SBW2TLRR/action/timestamp_anchor","attest_storage":"https://pith.science/pith/I4FKBSVDPDHK3K3YT6SBW2TLRR/action/storage_attestation","attest_author":"https://pith.science/pith/I4FKBSVDPDHK3K3YT6SBW2TLRR/action/author_attestation","sign_citation":"https://pith.science/pith/I4FKBSVDPDHK3K3YT6SBW2TLRR/action/citation_signature","submit_replication":"https://pith.science/pith/I4FKBSVDPDHK3K3YT6SBW2TLRR/action/replication_record"}},"created_at":"2026-05-17T23:51:59.507936+00:00","updated_at":"2026-05-17T23:51:59.507936+00:00"}