{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:56IPHP537UC76DJYAPGL3WEE4W","short_pith_number":"pith:56IPHP53","canonical_record":{"source":{"id":"1801.07233","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.NE","submitted_at":"2018-01-22T18:29:47Z","cross_cats_sorted":[],"title_canon_sha256":"d4f4647ad10a721d40c662f7d56d43bc282507a01dd4c7781b388370beb453be","abstract_canon_sha256":"60589cd41a01cd1d1ba073c486a35c1d5af5cf03ac1ecdab136e831c4d01d6c2"},"schema_version":"1.0"},"canonical_sha256":"ef90f3bfbbfd05ff0d3803ccbdd884e5a6ced3217495af529c87cbe6d868aba8","source":{"kind":"arxiv","id":"1801.07233","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1801.07233","created_at":"2026-05-18T00:25:21Z"},{"alias_kind":"arxiv_version","alias_value":"1801.07233v1","created_at":"2026-05-18T00:25:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1801.07233","created_at":"2026-05-18T00:25:21Z"},{"alias_kind":"pith_short_12","alias_value":"56IPHP537UC7","created_at":"2026-05-18T12:32:08Z"},{"alias_kind":"pith_short_16","alias_value":"56IPHP537UC76DJY","created_at":"2026-05-18T12:32:08Z"},{"alias_kind":"pith_short_8","alias_value":"56IPHP53","created_at":"2026-05-18T12:32:08Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:56IPHP537UC76DJYAPGL3WEE4W","target":"record","payload":{"canonical_record":{"source":{"id":"1801.07233","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.NE","submitted_at":"2018-01-22T18:29:47Z","cross_cats_sorted":[],"title_canon_sha256":"d4f4647ad10a721d40c662f7d56d43bc282507a01dd4c7781b388370beb453be","abstract_canon_sha256":"60589cd41a01cd1d1ba073c486a35c1d5af5cf03ac1ecdab136e831c4d01d6c2"},"schema_version":"1.0"},"canonical_sha256":"ef90f3bfbbfd05ff0d3803ccbdd884e5a6ced3217495af529c87cbe6d868aba8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:25:21.853870Z","signature_b64":"BnHfiH9OkwyB9yyN3Om4JB5CRDs7tmez/HCmDgaFLu0TycXluZZmuvu7AEZ8n9Iem8uIn508aQyTWWsK4brDBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ef90f3bfbbfd05ff0d3803ccbdd884e5a6ced3217495af529c87cbe6d868aba8","last_reissued_at":"2026-05-18T00:25:21.853212Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:25:21.853212Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1801.07233","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":"2026-05-18T00:25:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RrWFkwKl4fXcQ+EugkpcAItuiIbBQETxX8SBvEPgtt2vp5q6q1q/Gk1zP1LO26ljBmT5NpNrOLqS14KGlF6hDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-07T10:36:48.316529Z"},"content_sha256":"ccd0a8931942535c513f8c80995d869ae988fb484fed8833f16c2be9f0b5d535","schema_version":"1.0","event_id":"sha256:ccd0a8931942535c513f8c80995d869ae988fb484fed8833f16c2be9f0b5d535"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:56IPHP537UC76DJYAPGL3WEE4W","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Improving TSP Solutions Using GA with a New Hybrid Mutation Based on Knowledge and Randomness","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.NE","authors_text":"Ahmad B. A. Hassanat, Esra'a Alkafaween","submitted_at":"2018-01-22T18:29:47Z","abstract_excerpt":"Genetic algorithm (GA) is an efficient tool for solving optimization problems by evolving solutions, as it mimics the Darwinian theory of natural evolution. The mutation operator is one of the key success factors in GA, as it is considered the exploration operator of GA. Various mutation operators exist to solve hard combinatorial problems such as the TSP. In this paper, we propose a hybrid mutation operator called \"IRGIBNNM\", this mutation is a combination of two existing mutations, a knowledge-based mutation, and a random-based mutation. We also improve the existing \"select best mutation\" st"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1801.07233","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:25:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+OqAWo48ixvwrtztODbwYVVulqmp7auC1liVWbq9saH8dsqC8WnYQ2TceVmQ4rH1QtY43I+TOHzYG+LFZiDjBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-07T10:36:48.316963Z"},"content_sha256":"b88f87ce10adb667afdeef3e5bb49cc46499b47f43f6ef6f6e5c148471c313a3","schema_version":"1.0","event_id":"sha256:b88f87ce10adb667afdeef3e5bb49cc46499b47f43f6ef6f6e5c148471c313a3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/56IPHP537UC76DJYAPGL3WEE4W/bundle.json","state_url":"https://pith.science/pith/56IPHP537UC76DJYAPGL3WEE4W/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/56IPHP537UC76DJYAPGL3WEE4W/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":"2026-06-07T10:36:48Z","links":{"resolver":"https://pith.science/pith/56IPHP537UC76DJYAPGL3WEE4W","bundle":"https://pith.science/pith/56IPHP537UC76DJYAPGL3WEE4W/bundle.json","state":"https://pith.science/pith/56IPHP537UC76DJYAPGL3WEE4W/state.json","well_known_bundle":"https://pith.science/.well-known/pith/56IPHP537UC76DJYAPGL3WEE4W/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:56IPHP537UC76DJYAPGL3WEE4W","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":"60589cd41a01cd1d1ba073c486a35c1d5af5cf03ac1ecdab136e831c4d01d6c2","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.NE","submitted_at":"2018-01-22T18:29:47Z","title_canon_sha256":"d4f4647ad10a721d40c662f7d56d43bc282507a01dd4c7781b388370beb453be"},"schema_version":"1.0","source":{"id":"1801.07233","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1801.07233","created_at":"2026-05-18T00:25:21Z"},{"alias_kind":"arxiv_version","alias_value":"1801.07233v1","created_at":"2026-05-18T00:25:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1801.07233","created_at":"2026-05-18T00:25:21Z"},{"alias_kind":"pith_short_12","alias_value":"56IPHP537UC7","created_at":"2026-05-18T12:32:08Z"},{"alias_kind":"pith_short_16","alias_value":"56IPHP537UC76DJY","created_at":"2026-05-18T12:32:08Z"},{"alias_kind":"pith_short_8","alias_value":"56IPHP53","created_at":"2026-05-18T12:32:08Z"}],"graph_snapshots":[{"event_id":"sha256:b88f87ce10adb667afdeef3e5bb49cc46499b47f43f6ef6f6e5c148471c313a3","target":"graph","created_at":"2026-05-18T00:25:21Z","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"},"paper":{"abstract_excerpt":"Genetic algorithm (GA) is an efficient tool for solving optimization problems by evolving solutions, as it mimics the Darwinian theory of natural evolution. The mutation operator is one of the key success factors in GA, as it is considered the exploration operator of GA. Various mutation operators exist to solve hard combinatorial problems such as the TSP. In this paper, we propose a hybrid mutation operator called \"IRGIBNNM\", this mutation is a combination of two existing mutations, a knowledge-based mutation, and a random-based mutation. We also improve the existing \"select best mutation\" st","authors_text":"Ahmad B. A. Hassanat, Esra'a Alkafaween","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.NE","submitted_at":"2018-01-22T18:29:47Z","title":"Improving TSP Solutions Using GA with a New Hybrid Mutation Based on Knowledge and Randomness"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1801.07233","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:ccd0a8931942535c513f8c80995d869ae988fb484fed8833f16c2be9f0b5d535","target":"record","created_at":"2026-05-18T00:25:21Z","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":"60589cd41a01cd1d1ba073c486a35c1d5af5cf03ac1ecdab136e831c4d01d6c2","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.NE","submitted_at":"2018-01-22T18:29:47Z","title_canon_sha256":"d4f4647ad10a721d40c662f7d56d43bc282507a01dd4c7781b388370beb453be"},"schema_version":"1.0","source":{"id":"1801.07233","kind":"arxiv","version":1}},"canonical_sha256":"ef90f3bfbbfd05ff0d3803ccbdd884e5a6ced3217495af529c87cbe6d868aba8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ef90f3bfbbfd05ff0d3803ccbdd884e5a6ced3217495af529c87cbe6d868aba8","first_computed_at":"2026-05-18T00:25:21.853212Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:25:21.853212Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"BnHfiH9OkwyB9yyN3Om4JB5CRDs7tmez/HCmDgaFLu0TycXluZZmuvu7AEZ8n9Iem8uIn508aQyTWWsK4brDBg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:25:21.853870Z","signed_message":"canonical_sha256_bytes"},"source_id":"1801.07233","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ccd0a8931942535c513f8c80995d869ae988fb484fed8833f16c2be9f0b5d535","sha256:b88f87ce10adb667afdeef3e5bb49cc46499b47f43f6ef6f6e5c148471c313a3"],"state_sha256":"3d3223efec26206c3694ff7800fde6789d9203bc4a2229fff7c0adacbdc1fd67"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GR491OZD1n7PVxfQ++siMB9XtnW2GbPCgB/e1G1nU2tKIbLt47Z324aiDO+B4UeTvsyIuQtHQysA9tMio5qgDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-07T10:36:48.319908Z","bundle_sha256":"2195efc41799e930ea803983f2168b653ca0b21cfdf59b22180abf41f95557ef"}}