{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:UM5EELSKISOJPZHRCTZGZT6QFL","short_pith_number":"pith:UM5EELSK","canonical_record":{"source":{"id":"2210.11132","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2022-10-20T09:49:24Z","cross_cats_sorted":["cs.DM","cs.DS"],"title_canon_sha256":"c5a199699aebd9572c683411bf7541066e7e6bb9dc9ec5827feb91524bf41b46","abstract_canon_sha256":"76e69fa75d2cb0f9123459e060c88c544c05c83441636b4bba0c48fc533daadd"},"schema_version":"1.0"},"canonical_sha256":"a33a422e4a449c97e4f114f26ccfd02ac5c11fc1ef9509f2c830ceb6a1d8bf1b","source":{"kind":"arxiv","id":"2210.11132","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.11132","created_at":"2026-07-05T05:08:44Z"},{"alias_kind":"arxiv_version","alias_value":"2210.11132v1","created_at":"2026-07-05T05:08:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.11132","created_at":"2026-07-05T05:08:44Z"},{"alias_kind":"pith_short_12","alias_value":"UM5EELSKISOJ","created_at":"2026-07-05T05:08:44Z"},{"alias_kind":"pith_short_16","alias_value":"UM5EELSKISOJPZHR","created_at":"2026-07-05T05:08:44Z"},{"alias_kind":"pith_short_8","alias_value":"UM5EELSK","created_at":"2026-07-05T05:08:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:UM5EELSKISOJPZHRCTZGZT6QFL","target":"record","payload":{"canonical_record":{"source":{"id":"2210.11132","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2022-10-20T09:49:24Z","cross_cats_sorted":["cs.DM","cs.DS"],"title_canon_sha256":"c5a199699aebd9572c683411bf7541066e7e6bb9dc9ec5827feb91524bf41b46","abstract_canon_sha256":"76e69fa75d2cb0f9123459e060c88c544c05c83441636b4bba0c48fc533daadd"},"schema_version":"1.0"},"canonical_sha256":"a33a422e4a449c97e4f114f26ccfd02ac5c11fc1ef9509f2c830ceb6a1d8bf1b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:08:44.495478Z","signature_b64":"5uOHc/PCZtbDlq9uLO+FJjjO//sNzJtjrf7XOvPhewU+LAgMdwDoY/0RhFWm2kuRHgP7GEM6CF6CYFmPNwotBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a33a422e4a449c97e4f114f26ccfd02ac5c11fc1ef9509f2c830ceb6a1d8bf1b","last_reissued_at":"2026-07-05T05:08:44.495113Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:08:44.495113Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2210.11132","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:08:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yWpq3zeXuibhA7g3ybdrCRK9zCsnQIU/tNk7RcDqWh2I0JJ5Hu6Yd3MXkco6LwjZFyai5ATWTuOuw+lVnke4Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T13:36:24.564466Z"},"content_sha256":"128c5aefa1ab5f09ffa5b78e19fd9e66d7d7560cfe9aaacc9fa74afd268006dd","schema_version":"1.0","event_id":"sha256:128c5aefa1ab5f09ffa5b78e19fd9e66d7d7560cfe9aaacc9fa74afd268006dd"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:UM5EELSKISOJPZHRCTZGZT6QFL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A general model-and-run solver for multistage robust discrete linear optimization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DM","cs.DS"],"primary_cat":"math.OC","authors_text":"Michael Hartisch, Ulf Lorenz","submitted_at":"2022-10-20T09:49:24Z","abstract_excerpt":"The necessity to deal with uncertain data is a major challenge in decision making. Robust optimization emerged as one of the predominant paradigms to produce solutions that hedge against uncertainty. In order to obtain an even more realistic description of the underlying problem where the decision maker can react to newly disclosed information, multistage models can be used. However, due to their computational difficulty, multistage problems beyond two stages have received less attention and are often only addressed using approximation rather than optimization schemes. Even less attention is p"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.11132","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2210.11132/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:08:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JcE1PFN7E0iEvenEoiLCyGXU8P4WdTG+wp9AV8HPEfq2np7OkP6G+4H1uHuldH3TfZxfphAalnlHCdUfFW6yDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T13:36:24.565013Z"},"content_sha256":"e8a3df57ca53d87cc246a39659525f1f9a7326c9c744ed7e4ad1a9c58cdbd736","schema_version":"1.0","event_id":"sha256:e8a3df57ca53d87cc246a39659525f1f9a7326c9c744ed7e4ad1a9c58cdbd736"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UM5EELSKISOJPZHRCTZGZT6QFL/bundle.json","state_url":"https://pith.science/pith/UM5EELSKISOJPZHRCTZGZT6QFL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UM5EELSKISOJPZHRCTZGZT6QFL/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-10T13:36:24Z","links":{"resolver":"https://pith.science/pith/UM5EELSKISOJPZHRCTZGZT6QFL","bundle":"https://pith.science/pith/UM5EELSKISOJPZHRCTZGZT6QFL/bundle.json","state":"https://pith.science/pith/UM5EELSKISOJPZHRCTZGZT6QFL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UM5EELSKISOJPZHRCTZGZT6QFL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:UM5EELSKISOJPZHRCTZGZT6QFL","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"76e69fa75d2cb0f9123459e060c88c544c05c83441636b4bba0c48fc533daadd","cross_cats_sorted":["cs.DM","cs.DS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2022-10-20T09:49:24Z","title_canon_sha256":"c5a199699aebd9572c683411bf7541066e7e6bb9dc9ec5827feb91524bf41b46"},"schema_version":"1.0","source":{"id":"2210.11132","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.11132","created_at":"2026-07-05T05:08:44Z"},{"alias_kind":"arxiv_version","alias_value":"2210.11132v1","created_at":"2026-07-05T05:08:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.11132","created_at":"2026-07-05T05:08:44Z"},{"alias_kind":"pith_short_12","alias_value":"UM5EELSKISOJ","created_at":"2026-07-05T05:08:44Z"},{"alias_kind":"pith_short_16","alias_value":"UM5EELSKISOJPZHR","created_at":"2026-07-05T05:08:44Z"},{"alias_kind":"pith_short_8","alias_value":"UM5EELSK","created_at":"2026-07-05T05:08:44Z"}],"graph_snapshots":[{"event_id":"sha256:e8a3df57ca53d87cc246a39659525f1f9a7326c9c744ed7e4ad1a9c58cdbd736","target":"graph","created_at":"2026-07-05T05:08:44Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2210.11132/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The necessity to deal with uncertain data is a major challenge in decision making. Robust optimization emerged as one of the predominant paradigms to produce solutions that hedge against uncertainty. In order to obtain an even more realistic description of the underlying problem where the decision maker can react to newly disclosed information, multistage models can be used. However, due to their computational difficulty, multistage problems beyond two stages have received less attention and are often only addressed using approximation rather than optimization schemes. Even less attention is p","authors_text":"Michael Hartisch, Ulf Lorenz","cross_cats":["cs.DM","cs.DS"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2022-10-20T09:49:24Z","title":"A general model-and-run solver for multistage robust discrete linear optimization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.11132","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:128c5aefa1ab5f09ffa5b78e19fd9e66d7d7560cfe9aaacc9fa74afd268006dd","target":"record","created_at":"2026-07-05T05:08:44Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"76e69fa75d2cb0f9123459e060c88c544c05c83441636b4bba0c48fc533daadd","cross_cats_sorted":["cs.DM","cs.DS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2022-10-20T09:49:24Z","title_canon_sha256":"c5a199699aebd9572c683411bf7541066e7e6bb9dc9ec5827feb91524bf41b46"},"schema_version":"1.0","source":{"id":"2210.11132","kind":"arxiv","version":1}},"canonical_sha256":"a33a422e4a449c97e4f114f26ccfd02ac5c11fc1ef9509f2c830ceb6a1d8bf1b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a33a422e4a449c97e4f114f26ccfd02ac5c11fc1ef9509f2c830ceb6a1d8bf1b","first_computed_at":"2026-07-05T05:08:44.495113Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:08:44.495113Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5uOHc/PCZtbDlq9uLO+FJjjO//sNzJtjrf7XOvPhewU+LAgMdwDoY/0RhFWm2kuRHgP7GEM6CF6CYFmPNwotBg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:08:44.495478Z","signed_message":"canonical_sha256_bytes"},"source_id":"2210.11132","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:128c5aefa1ab5f09ffa5b78e19fd9e66d7d7560cfe9aaacc9fa74afd268006dd","sha256:e8a3df57ca53d87cc246a39659525f1f9a7326c9c744ed7e4ad1a9c58cdbd736"],"state_sha256":"2dbc20d36399ff60accc47c6dc2987bd6e03bb7e23fd94a0dadfc2be6c535116"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AC1R8itAs/CSlZYVfnB92AH8R/K4MTjxAhqZToJYrys+hlWr3UzYsUQQFnlb0B8+Ukj90b91pfnTX/O9hb4FBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T13:36:24.570338Z","bundle_sha256":"e6388782062227669fa130a2bd0886171fe18d34dd9bc9d5949ef18bcc6f7220"}}