{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:KGV6ULP7ML2RKCHGKTGKQHWXFV","short_pith_number":"pith:KGV6ULP7","schema_version":"1.0","canonical_sha256":"51abea2dff62f51508e654cca81ed72d722ca0566ff05c8d1f836024efc3cba8","source":{"kind":"arxiv","id":"1703.03155","version":1},"attestation_state":"computed","paper":{"title":"Conic relaxation approaches for equal deployment problems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.OC","authors_text":"Makoto Yamashita, Satoko Moriguchi, Sena Safarina, Tim J. Mullin","submitted_at":"2017-03-09T06:47:01Z","abstract_excerpt":"An important problem in the breeding of livestock, crops, and forest trees is the optimum of selection of genotypes that maximizes genetic gain. The key constraint in the optimal selection is a convex quadratic constraint that ensures genetic diversity, therefore, the optimal selection can be cast as a second-order cone programming (SOCP) problem. Yamashita et al. (2015) exploits the structural sparsity of the quadratic constraints and reduces the computation time drastically while attaining the same optimal solution.\n  This paper is concerned with the special case of equal deployment (ED), in"},"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":"1703.03155","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2017-03-09T06:47:01Z","cross_cats_sorted":[],"title_canon_sha256":"2bc442d4aef309befdb717d4ee29245635efc5205d36ba89b09c00e4356943d9","abstract_canon_sha256":"d30855bae2d147c9c3fe0af8b71b0a88cbfd86986c4747ba72d070f55107fe5f"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:49:01.293756Z","signature_b64":"OLLaNqvv4VOTaajde+4G18JgMW/cAVnCPFftDnKQG+ImrXX1qQ6/l5vQt8tuYGDNTVJaGfsg8L0tanSnOy6JBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"51abea2dff62f51508e654cca81ed72d722ca0566ff05c8d1f836024efc3cba8","last_reissued_at":"2026-05-18T00:49:01.293016Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:49:01.293016Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Conic relaxation approaches for equal deployment problems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.OC","authors_text":"Makoto Yamashita, Satoko Moriguchi, Sena Safarina, Tim J. Mullin","submitted_at":"2017-03-09T06:47:01Z","abstract_excerpt":"An important problem in the breeding of livestock, crops, and forest trees is the optimum of selection of genotypes that maximizes genetic gain. The key constraint in the optimal selection is a convex quadratic constraint that ensures genetic diversity, therefore, the optimal selection can be cast as a second-order cone programming (SOCP) problem. Yamashita et al. (2015) exploits the structural sparsity of the quadratic constraints and reduces the computation time drastically while attaining the same optimal solution.\n  This paper is concerned with the special case of equal deployment (ED), in"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1703.03155","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":"1703.03155","created_at":"2026-05-18T00:49:01.293142+00:00"},{"alias_kind":"arxiv_version","alias_value":"1703.03155v1","created_at":"2026-05-18T00:49:01.293142+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1703.03155","created_at":"2026-05-18T00:49:01.293142+00:00"},{"alias_kind":"pith_short_12","alias_value":"KGV6ULP7ML2R","created_at":"2026-05-18T12:31:24.725408+00:00"},{"alias_kind":"pith_short_16","alias_value":"KGV6ULP7ML2RKCHG","created_at":"2026-05-18T12:31:24.725408+00:00"},{"alias_kind":"pith_short_8","alias_value":"KGV6ULP7","created_at":"2026-05-18T12:31:24.725408+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/KGV6ULP7ML2RKCHGKTGKQHWXFV","json":"https://pith.science/pith/KGV6ULP7ML2RKCHGKTGKQHWXFV.json","graph_json":"https://pith.science/api/pith-number/KGV6ULP7ML2RKCHGKTGKQHWXFV/graph.json","events_json":"https://pith.science/api/pith-number/KGV6ULP7ML2RKCHGKTGKQHWXFV/events.json","paper":"https://pith.science/paper/KGV6ULP7"},"agent_actions":{"view_html":"https://pith.science/pith/KGV6ULP7ML2RKCHGKTGKQHWXFV","download_json":"https://pith.science/pith/KGV6ULP7ML2RKCHGKTGKQHWXFV.json","view_paper":"https://pith.science/paper/KGV6ULP7","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1703.03155&json=true","fetch_graph":"https://pith.science/api/pith-number/KGV6ULP7ML2RKCHGKTGKQHWXFV/graph.json","fetch_events":"https://pith.science/api/pith-number/KGV6ULP7ML2RKCHGKTGKQHWXFV/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/KGV6ULP7ML2RKCHGKTGKQHWXFV/action/timestamp_anchor","attest_storage":"https://pith.science/pith/KGV6ULP7ML2RKCHGKTGKQHWXFV/action/storage_attestation","attest_author":"https://pith.science/pith/KGV6ULP7ML2RKCHGKTGKQHWXFV/action/author_attestation","sign_citation":"https://pith.science/pith/KGV6ULP7ML2RKCHGKTGKQHWXFV/action/citation_signature","submit_replication":"https://pith.science/pith/KGV6ULP7ML2RKCHGKTGKQHWXFV/action/replication_record"}},"created_at":"2026-05-18T00:49:01.293142+00:00","updated_at":"2026-05-18T00:49:01.293142+00:00"}