{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:GY2PSCUNGWHHTG5BCIAJW5CCLZ","short_pith_number":"pith:GY2PSCUN","schema_version":"1.0","canonical_sha256":"3634f90a8d358e799ba112009b74425e62a4b1f8b1e5ce042737f51cd7c07905","source":{"kind":"arxiv","id":"2111.10188","version":2},"attestation_state":"computed","paper":{"title":"HMS-OS: Improving the Human Mental Search Optimisation Algorithm by Grouping in both Search and Objective Space","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.NE","authors_text":"Diego Oliva, Gerald Schaefer, Iakov Korovin, Mahshid Helali Moghadam, Mehrdad Saadatmand, Seyed Jalaleddin Mousavirad","submitted_at":"2021-11-19T12:56:33Z","abstract_excerpt":"The human mental search (HMS) algorithm is a relatively recent population-based metaheuristic algorithm, which has shown competitive performance in solving complex optimisation problems. It is based on three main operators: mental search, grouping, and movement. In the original HMS algorithm, a clustering algorithm is used to group the current population in order to identify a promising region in search space, while candidate solutions then move towards the best candidate solution in the promising region. In this paper, we propose a novel HMS algorithm, HMS-OS, which is based on clustering 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":"2111.10188","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2021-11-19T12:56:33Z","cross_cats_sorted":[],"title_canon_sha256":"0493fb38af3073015bbce07a532cc95f186f60597fdffb7306da7d8da7eb1659","abstract_canon_sha256":"74ea81cc397e3faefc2cacd452e84d7cc7e43d6152675b2d91f978f47c34fe9a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:37:29.766294Z","signature_b64":"vuY5itPl/Byl7nk2iMBgQ7gsPTWlnMdASlBAaFSnBp/7EqSFGlx8aDfigQteyLUSVrqjTO2qLZ4HtOZjVLzjBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3634f90a8d358e799ba112009b74425e62a4b1f8b1e5ce042737f51cd7c07905","last_reissued_at":"2026-07-05T03:37:29.765861Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:37:29.765861Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"HMS-OS: Improving the Human Mental Search Optimisation Algorithm by Grouping in both Search and Objective Space","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.NE","authors_text":"Diego Oliva, Gerald Schaefer, Iakov Korovin, Mahshid Helali Moghadam, Mehrdad Saadatmand, Seyed Jalaleddin Mousavirad","submitted_at":"2021-11-19T12:56:33Z","abstract_excerpt":"The human mental search (HMS) algorithm is a relatively recent population-based metaheuristic algorithm, which has shown competitive performance in solving complex optimisation problems. It is based on three main operators: mental search, grouping, and movement. In the original HMS algorithm, a clustering algorithm is used to group the current population in order to identify a promising region in search space, while candidate solutions then move towards the best candidate solution in the promising region. In this paper, we propose a novel HMS algorithm, HMS-OS, which is based on clustering in "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2111.10188","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2111.10188/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":"2111.10188","created_at":"2026-07-05T03:37:29.765927+00:00"},{"alias_kind":"arxiv_version","alias_value":"2111.10188v2","created_at":"2026-07-05T03:37:29.765927+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2111.10188","created_at":"2026-07-05T03:37:29.765927+00:00"},{"alias_kind":"pith_short_12","alias_value":"GY2PSCUNGWHH","created_at":"2026-07-05T03:37:29.765927+00:00"},{"alias_kind":"pith_short_16","alias_value":"GY2PSCUNGWHHTG5B","created_at":"2026-07-05T03:37:29.765927+00:00"},{"alias_kind":"pith_short_8","alias_value":"GY2PSCUN","created_at":"2026-07-05T03:37:29.765927+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/GY2PSCUNGWHHTG5BCIAJW5CCLZ","json":"https://pith.science/pith/GY2PSCUNGWHHTG5BCIAJW5CCLZ.json","graph_json":"https://pith.science/api/pith-number/GY2PSCUNGWHHTG5BCIAJW5CCLZ/graph.json","events_json":"https://pith.science/api/pith-number/GY2PSCUNGWHHTG5BCIAJW5CCLZ/events.json","paper":"https://pith.science/paper/GY2PSCUN"},"agent_actions":{"view_html":"https://pith.science/pith/GY2PSCUNGWHHTG5BCIAJW5CCLZ","download_json":"https://pith.science/pith/GY2PSCUNGWHHTG5BCIAJW5CCLZ.json","view_paper":"https://pith.science/paper/GY2PSCUN","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2111.10188&json=true","fetch_graph":"https://pith.science/api/pith-number/GY2PSCUNGWHHTG5BCIAJW5CCLZ/graph.json","fetch_events":"https://pith.science/api/pith-number/GY2PSCUNGWHHTG5BCIAJW5CCLZ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/GY2PSCUNGWHHTG5BCIAJW5CCLZ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/GY2PSCUNGWHHTG5BCIAJW5CCLZ/action/storage_attestation","attest_author":"https://pith.science/pith/GY2PSCUNGWHHTG5BCIAJW5CCLZ/action/author_attestation","sign_citation":"https://pith.science/pith/GY2PSCUNGWHHTG5BCIAJW5CCLZ/action/citation_signature","submit_replication":"https://pith.science/pith/GY2PSCUNGWHHTG5BCIAJW5CCLZ/action/replication_record"}},"created_at":"2026-07-05T03:37:29.765927+00:00","updated_at":"2026-07-05T03:37:29.765927+00:00"}