{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:GZ6FFCJO2ETSRH4UYMBFCHENQY","short_pith_number":"pith:GZ6FFCJO","schema_version":"1.0","canonical_sha256":"367c52892ed127289f94c302511c8d860eedcb0e61487b15cefca40dd1e000dd","source":{"kind":"arxiv","id":"1803.06034","version":5},"attestation_state":"computed","paper":{"title":"Multistage stochastic programs with a random number of stages: dynamic programming equations, solution methods, and application to portfolio selection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.OC","authors_text":"Vincent Guigues","submitted_at":"2018-03-15T23:35:57Z","abstract_excerpt":"We introduce the class of multistage stochastic optimization problems with a random number of stages. For such problems, we show how to write dynamic programming equations and detail the Stochastic Dual Dynamic Programming algorithm to solve these equations. Finally, we consider a portfolio selection problem over an optimization period of random duration. For several instances of this problem, we show the gain obtained using a policy that takes the random duration of the number of stages into account over a policy built taking a fixed number of stages (namely the maximal possible number of sta"},"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":"1803.06034","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2018-03-15T23:35:57Z","cross_cats_sorted":[],"title_canon_sha256":"6939683ea83708103e1e894ff362be820ae54762eb903426476b7e3b9bc387b7","abstract_canon_sha256":"b18b85eb2921d5b27638a18a6e6815882a327a1971edd30cd77ae88e6d3e7101"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:40:24.241741Z","signature_b64":"TGajzcGryA8GISRPayT0YVvp6ITYFW4sA/BuQZw1rVLPrim2BnvOKdy+vr4cg0c6qBoqZvPPeUViptg7h4UxAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"367c52892ed127289f94c302511c8d860eedcb0e61487b15cefca40dd1e000dd","last_reissued_at":"2026-05-17T23:40:24.240931Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:40:24.240931Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Multistage stochastic programs with a random number of stages: dynamic programming equations, solution methods, and application to portfolio selection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.OC","authors_text":"Vincent Guigues","submitted_at":"2018-03-15T23:35:57Z","abstract_excerpt":"We introduce the class of multistage stochastic optimization problems with a random number of stages. For such problems, we show how to write dynamic programming equations and detail the Stochastic Dual Dynamic Programming algorithm to solve these equations. Finally, we consider a portfolio selection problem over an optimization period of random duration. For several instances of this problem, we show the gain obtained using a policy that takes the random duration of the number of stages into account over a policy built taking a fixed number of stages (namely the maximal possible number of sta"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1803.06034","kind":"arxiv","version":5},"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":"1803.06034","created_at":"2026-05-17T23:40:24.241028+00:00"},{"alias_kind":"arxiv_version","alias_value":"1803.06034v5","created_at":"2026-05-17T23:40:24.241028+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1803.06034","created_at":"2026-05-17T23:40:24.241028+00:00"},{"alias_kind":"pith_short_12","alias_value":"GZ6FFCJO2ETS","created_at":"2026-05-18T12:32:25.280505+00:00"},{"alias_kind":"pith_short_16","alias_value":"GZ6FFCJO2ETSRH4U","created_at":"2026-05-18T12:32:25.280505+00:00"},{"alias_kind":"pith_short_8","alias_value":"GZ6FFCJO","created_at":"2026-05-18T12:32:25.280505+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/GZ6FFCJO2ETSRH4UYMBFCHENQY","json":"https://pith.science/pith/GZ6FFCJO2ETSRH4UYMBFCHENQY.json","graph_json":"https://pith.science/api/pith-number/GZ6FFCJO2ETSRH4UYMBFCHENQY/graph.json","events_json":"https://pith.science/api/pith-number/GZ6FFCJO2ETSRH4UYMBFCHENQY/events.json","paper":"https://pith.science/paper/GZ6FFCJO"},"agent_actions":{"view_html":"https://pith.science/pith/GZ6FFCJO2ETSRH4UYMBFCHENQY","download_json":"https://pith.science/pith/GZ6FFCJO2ETSRH4UYMBFCHENQY.json","view_paper":"https://pith.science/paper/GZ6FFCJO","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1803.06034&json=true","fetch_graph":"https://pith.science/api/pith-number/GZ6FFCJO2ETSRH4UYMBFCHENQY/graph.json","fetch_events":"https://pith.science/api/pith-number/GZ6FFCJO2ETSRH4UYMBFCHENQY/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/GZ6FFCJO2ETSRH4UYMBFCHENQY/action/timestamp_anchor","attest_storage":"https://pith.science/pith/GZ6FFCJO2ETSRH4UYMBFCHENQY/action/storage_attestation","attest_author":"https://pith.science/pith/GZ6FFCJO2ETSRH4UYMBFCHENQY/action/author_attestation","sign_citation":"https://pith.science/pith/GZ6FFCJO2ETSRH4UYMBFCHENQY/action/citation_signature","submit_replication":"https://pith.science/pith/GZ6FFCJO2ETSRH4UYMBFCHENQY/action/replication_record"}},"created_at":"2026-05-17T23:40:24.241028+00:00","updated_at":"2026-05-17T23:40:24.241028+00:00"}