{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2014:3Y5X2OSBKVQPEESONXM3KOWCTT","short_pith_number":"pith:3Y5X2OSB","schema_version":"1.0","canonical_sha256":"de3b7d3a415560f2124e6dd9b53ac29ccce86d1c285e50f59a42ca1ef25cee4f","source":{"kind":"arxiv","id":"1407.4000","version":2},"attestation_state":"computed","paper":{"title":"Uncertainty And Evolutionary Optimization: A Novel Approach","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.NE","authors_text":"A. Mahmood, Maumita Bhattacharya, R. Islam","submitted_at":"2014-07-15T14:05:24Z","abstract_excerpt":"Evolutionary algorithms (EA) have been widely accepted as efficient solvers for complex real world optimization problems, including engineering optimization. However, real world optimization problems often involve uncertain environment including noisy and/or dynamic environments, which pose major challenges to EA-based optimization. The presence of noise interferes with the evaluation and the selection process of EA, and thus adversely affects its performance. In addition, as presence of noise poses challenges to the evaluation of the fitness function, it may need to be estimated instead of be"},"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":"1407.4000","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2014-07-15T14:05:24Z","cross_cats_sorted":[],"title_canon_sha256":"6c7617eaa6a2e4d638a841f4a5fdf1f1f5ea05ea85d9eb0bbd5d34721a9a9867","abstract_canon_sha256":"300d176fb7e4031ae553c04bd2c4e681dd7218384bfa2e8d1f4da03c392ec855"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:58:41.261883Z","signature_b64":"IfGINRYhmSa8X9Ifd1ltwx/y9UCvvKJAi16VS7RAJeXcXw0r7TVn+v1NespcG5jcRz0c5a0qTS+00Bg8+5sWCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"de3b7d3a415560f2124e6dd9b53ac29ccce86d1c285e50f59a42ca1ef25cee4f","last_reissued_at":"2026-05-18T00:58:41.261128Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:58:41.261128Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Uncertainty And Evolutionary Optimization: A Novel Approach","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.NE","authors_text":"A. Mahmood, Maumita Bhattacharya, R. Islam","submitted_at":"2014-07-15T14:05:24Z","abstract_excerpt":"Evolutionary algorithms (EA) have been widely accepted as efficient solvers for complex real world optimization problems, including engineering optimization. However, real world optimization problems often involve uncertain environment including noisy and/or dynamic environments, which pose major challenges to EA-based optimization. The presence of noise interferes with the evaluation and the selection process of EA, and thus adversely affects its performance. In addition, as presence of noise poses challenges to the evaluation of the fitness function, it may need to be estimated instead of be"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1407.4000","kind":"arxiv","version":2},"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":"1407.4000","created_at":"2026-05-18T00:58:41.261263+00:00"},{"alias_kind":"arxiv_version","alias_value":"1407.4000v2","created_at":"2026-05-18T00:58:41.261263+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1407.4000","created_at":"2026-05-18T00:58:41.261263+00:00"},{"alias_kind":"pith_short_12","alias_value":"3Y5X2OSBKVQP","created_at":"2026-05-18T12:28:11.866339+00:00"},{"alias_kind":"pith_short_16","alias_value":"3Y5X2OSBKVQPEESO","created_at":"2026-05-18T12:28:11.866339+00:00"},{"alias_kind":"pith_short_8","alias_value":"3Y5X2OSB","created_at":"2026-05-18T12:28:11.866339+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/3Y5X2OSBKVQPEESONXM3KOWCTT","json":"https://pith.science/pith/3Y5X2OSBKVQPEESONXM3KOWCTT.json","graph_json":"https://pith.science/api/pith-number/3Y5X2OSBKVQPEESONXM3KOWCTT/graph.json","events_json":"https://pith.science/api/pith-number/3Y5X2OSBKVQPEESONXM3KOWCTT/events.json","paper":"https://pith.science/paper/3Y5X2OSB"},"agent_actions":{"view_html":"https://pith.science/pith/3Y5X2OSBKVQPEESONXM3KOWCTT","download_json":"https://pith.science/pith/3Y5X2OSBKVQPEESONXM3KOWCTT.json","view_paper":"https://pith.science/paper/3Y5X2OSB","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1407.4000&json=true","fetch_graph":"https://pith.science/api/pith-number/3Y5X2OSBKVQPEESONXM3KOWCTT/graph.json","fetch_events":"https://pith.science/api/pith-number/3Y5X2OSBKVQPEESONXM3KOWCTT/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/3Y5X2OSBKVQPEESONXM3KOWCTT/action/timestamp_anchor","attest_storage":"https://pith.science/pith/3Y5X2OSBKVQPEESONXM3KOWCTT/action/storage_attestation","attest_author":"https://pith.science/pith/3Y5X2OSBKVQPEESONXM3KOWCTT/action/author_attestation","sign_citation":"https://pith.science/pith/3Y5X2OSBKVQPEESONXM3KOWCTT/action/citation_signature","submit_replication":"https://pith.science/pith/3Y5X2OSBKVQPEESONXM3KOWCTT/action/replication_record"}},"created_at":"2026-05-18T00:58:41.261263+00:00","updated_at":"2026-05-18T00:58:41.261263+00:00"}