{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:5G2IPNRCLLMTKDJYHDW4YS2Y6S","short_pith_number":"pith:5G2IPNRC","schema_version":"1.0","canonical_sha256":"e9b487b6225ad9350d3838edcc4b58f4bc1c769ebdd4bca0e8a3d8298f599125","source":{"kind":"arxiv","id":"2205.02307","version":3},"attestation_state":"computed","paper":{"title":"BilevelJuMP.jl: Modeling and Solving Bilevel Optimization in Julia","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.MS"],"primary_cat":"math.OC","authors_text":"Alexandre Street, Guilherme Bodin, Joaquim Dias Garcia","submitted_at":"2022-05-04T20:00:51Z","abstract_excerpt":"In this paper we present BilevelJuMP, a new Julia package to support bilevel optimization within the JuMP framework. The package is a Julia library that enables the user to describe both upper and lower-level optimization problems using the JuMP algebraic syntax. Due to the generality and flexibility our library inherits from JuMP's syntax, our package allows users to model bilevel optimization problems with conic constraints in the lower level and all JuMP supported constraints in the upper level (Conic, Quadratic, Non-Linear, Integer, etc.). Moreover, the user-defined problem can be subseque"},"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":"2205.02307","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2022-05-04T20:00:51Z","cross_cats_sorted":["cs.MS"],"title_canon_sha256":"b3c89a75d55ae76158d3c2046155ed5be2698e164c290b9bbaf511df3c1e4a49","abstract_canon_sha256":"189eb6c5d4c67472c69427bc1239fd5fa510deb3815be0732a8e36ce19a5278b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:26:41.176536Z","signature_b64":"Oa7P9BOozvrv5spzHGXihJZd0lXzuBppW5nTr1efswJ/yqOcOhBkIPXrdawOr+U5h7nN8W0QCrxsvbvcadFhDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e9b487b6225ad9350d3838edcc4b58f4bc1c769ebdd4bca0e8a3d8298f599125","last_reissued_at":"2026-07-05T05:26:41.176048Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:26:41.176048Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"BilevelJuMP.jl: Modeling and Solving Bilevel Optimization in Julia","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.MS"],"primary_cat":"math.OC","authors_text":"Alexandre Street, Guilherme Bodin, Joaquim Dias Garcia","submitted_at":"2022-05-04T20:00:51Z","abstract_excerpt":"In this paper we present BilevelJuMP, a new Julia package to support bilevel optimization within the JuMP framework. The package is a Julia library that enables the user to describe both upper and lower-level optimization problems using the JuMP algebraic syntax. Due to the generality and flexibility our library inherits from JuMP's syntax, our package allows users to model bilevel optimization problems with conic constraints in the lower level and all JuMP supported constraints in the upper level (Conic, Quadratic, Non-Linear, Integer, etc.). Moreover, the user-defined problem can be subseque"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.02307","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2205.02307/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2205.02307","created_at":"2026-07-05T05:26:41.176103+00:00"},{"alias_kind":"arxiv_version","alias_value":"2205.02307v3","created_at":"2026-07-05T05:26:41.176103+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.02307","created_at":"2026-07-05T05:26:41.176103+00:00"},{"alias_kind":"pith_short_12","alias_value":"5G2IPNRCLLMT","created_at":"2026-07-05T05:26:41.176103+00:00"},{"alias_kind":"pith_short_16","alias_value":"5G2IPNRCLLMTKDJY","created_at":"2026-07-05T05:26:41.176103+00:00"},{"alias_kind":"pith_short_8","alias_value":"5G2IPNRC","created_at":"2026-07-05T05:26:41.176103+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/5G2IPNRCLLMTKDJYHDW4YS2Y6S","json":"https://pith.science/pith/5G2IPNRCLLMTKDJYHDW4YS2Y6S.json","graph_json":"https://pith.science/api/pith-number/5G2IPNRCLLMTKDJYHDW4YS2Y6S/graph.json","events_json":"https://pith.science/api/pith-number/5G2IPNRCLLMTKDJYHDW4YS2Y6S/events.json","paper":"https://pith.science/paper/5G2IPNRC"},"agent_actions":{"view_html":"https://pith.science/pith/5G2IPNRCLLMTKDJYHDW4YS2Y6S","download_json":"https://pith.science/pith/5G2IPNRCLLMTKDJYHDW4YS2Y6S.json","view_paper":"https://pith.science/paper/5G2IPNRC","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2205.02307&json=true","fetch_graph":"https://pith.science/api/pith-number/5G2IPNRCLLMTKDJYHDW4YS2Y6S/graph.json","fetch_events":"https://pith.science/api/pith-number/5G2IPNRCLLMTKDJYHDW4YS2Y6S/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/5G2IPNRCLLMTKDJYHDW4YS2Y6S/action/timestamp_anchor","attest_storage":"https://pith.science/pith/5G2IPNRCLLMTKDJYHDW4YS2Y6S/action/storage_attestation","attest_author":"https://pith.science/pith/5G2IPNRCLLMTKDJYHDW4YS2Y6S/action/author_attestation","sign_citation":"https://pith.science/pith/5G2IPNRCLLMTKDJYHDW4YS2Y6S/action/citation_signature","submit_replication":"https://pith.science/pith/5G2IPNRCLLMTKDJYHDW4YS2Y6S/action/replication_record"}},"created_at":"2026-07-05T05:26:41.176103+00:00","updated_at":"2026-07-05T05:26:41.176103+00:00"}