{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2014:A44FS7Q2PKOUY7H4AV5CZDLMYY","short_pith_number":"pith:A44FS7Q2","canonical_record":{"source":{"id":"1401.1124","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2014-01-06T15:54:16Z","cross_cats_sorted":[],"title_canon_sha256":"6bc451d44f4ca8e5bab0ff7dbddcdb2889ef498be7e2d1b48477dd1a8b578e24","abstract_canon_sha256":"46a2fdaf33bcad7f556c5d64145c71b076919e341bc4f9229c983e0930070fda"},"schema_version":"1.0"},"canonical_sha256":"0738597e1a7a9d4c7cfc057a2c8d6cc62dd789b68e841589f8eb114dacccb5eb","source":{"kind":"arxiv","id":"1401.1124","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1401.1124","created_at":"2026-05-18T02:52:06Z"},{"alias_kind":"arxiv_version","alias_value":"1401.1124v2","created_at":"2026-05-18T02:52:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1401.1124","created_at":"2026-05-18T02:52:06Z"},{"alias_kind":"pith_short_12","alias_value":"A44FS7Q2PKOU","created_at":"2026-05-18T12:28:19Z"},{"alias_kind":"pith_short_16","alias_value":"A44FS7Q2PKOUY7H4","created_at":"2026-05-18T12:28:19Z"},{"alias_kind":"pith_short_8","alias_value":"A44FS7Q2","created_at":"2026-05-18T12:28:19Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2014:A44FS7Q2PKOUY7H4AV5CZDLMYY","target":"record","payload":{"canonical_record":{"source":{"id":"1401.1124","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2014-01-06T15:54:16Z","cross_cats_sorted":[],"title_canon_sha256":"6bc451d44f4ca8e5bab0ff7dbddcdb2889ef498be7e2d1b48477dd1a8b578e24","abstract_canon_sha256":"46a2fdaf33bcad7f556c5d64145c71b076919e341bc4f9229c983e0930070fda"},"schema_version":"1.0"},"canonical_sha256":"0738597e1a7a9d4c7cfc057a2c8d6cc62dd789b68e841589f8eb114dacccb5eb","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:52:06.221078Z","signature_b64":"8RMGqkpW+0Dxs4M72vd/kAZDzbY8HBUzNh8wKaOytby/BevgE2ZZ0/SCo1VAx380uyatw+4mnn7mWbgar9pQAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0738597e1a7a9d4c7cfc057a2c8d6cc62dd789b68e841589f8eb114dacccb5eb","last_reissued_at":"2026-05-18T02:52:06.220471Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:52:06.220471Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1401.1124","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T02:52:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HT/qlikvWXXCtadJPrdbalQITdwQi4zL8Pa5O2CaN+Wep9eUAnpI2Z9m00iVo6725x6t0GuMjsvkG4AkbN+3DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-09T06:52:04.586255Z"},"content_sha256":"4dafa3cab1fcdbc8d6498c755ac87df04080009573f1afea08842984cbea3f97","schema_version":"1.0","event_id":"sha256:4dafa3cab1fcdbc8d6498c755ac87df04080009573f1afea08842984cbea3f97"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2014:A44FS7Q2PKOUY7H4AV5CZDLMYY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A binary differential evolution algorithm learning from explored solutions","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.NE","authors_text":"Weicheng Xie, Xiufen Zou, Yu Chen","submitted_at":"2014-01-06T15:54:16Z","abstract_excerpt":"Although real-coded differential evolution (DE) algorithms can perform well on continuous optimization problems (CoOPs), it is still a challenging task to design an efficient binary-coded DE algorithm. Inspired by the learning mechanism of particle swarm optimization (PSO) algorithms, we propose a binary learning differential evolution (BLDE) algorithm that can efficiently locate the global optimal solutions by learning from the last population. Then, we theoretically prove the global convergence of BLDE, and compare it with some existing binary-coded evolutionary algorithms (EAs) via numerica"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1401.1124","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T02:52:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VCEeBsImVxGfe1utv3AI/hfQSXoztglJxXsjC4qfEU3aAi9PuXy1czNotskZRZa21ORrf4MvmgivPxIMIKg8Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-09T06:52:04.586915Z"},"content_sha256":"4280fcb821d706b41f233304c38cacb81893db3eea523be0ae3abe5e70aae904","schema_version":"1.0","event_id":"sha256:4280fcb821d706b41f233304c38cacb81893db3eea523be0ae3abe5e70aae904"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/A44FS7Q2PKOUY7H4AV5CZDLMYY/bundle.json","state_url":"https://pith.science/pith/A44FS7Q2PKOUY7H4AV5CZDLMYY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/A44FS7Q2PKOUY7H4AV5CZDLMYY/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":"2026-06-09T06:52:04Z","links":{"resolver":"https://pith.science/pith/A44FS7Q2PKOUY7H4AV5CZDLMYY","bundle":"https://pith.science/pith/A44FS7Q2PKOUY7H4AV5CZDLMYY/bundle.json","state":"https://pith.science/pith/A44FS7Q2PKOUY7H4AV5CZDLMYY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/A44FS7Q2PKOUY7H4AV5CZDLMYY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2014:A44FS7Q2PKOUY7H4AV5CZDLMYY","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":"46a2fdaf33bcad7f556c5d64145c71b076919e341bc4f9229c983e0930070fda","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2014-01-06T15:54:16Z","title_canon_sha256":"6bc451d44f4ca8e5bab0ff7dbddcdb2889ef498be7e2d1b48477dd1a8b578e24"},"schema_version":"1.0","source":{"id":"1401.1124","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1401.1124","created_at":"2026-05-18T02:52:06Z"},{"alias_kind":"arxiv_version","alias_value":"1401.1124v2","created_at":"2026-05-18T02:52:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1401.1124","created_at":"2026-05-18T02:52:06Z"},{"alias_kind":"pith_short_12","alias_value":"A44FS7Q2PKOU","created_at":"2026-05-18T12:28:19Z"},{"alias_kind":"pith_short_16","alias_value":"A44FS7Q2PKOUY7H4","created_at":"2026-05-18T12:28:19Z"},{"alias_kind":"pith_short_8","alias_value":"A44FS7Q2","created_at":"2026-05-18T12:28:19Z"}],"graph_snapshots":[{"event_id":"sha256:4280fcb821d706b41f233304c38cacb81893db3eea523be0ae3abe5e70aae904","target":"graph","created_at":"2026-05-18T02:52:06Z","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":"Although real-coded differential evolution (DE) algorithms can perform well on continuous optimization problems (CoOPs), it is still a challenging task to design an efficient binary-coded DE algorithm. Inspired by the learning mechanism of particle swarm optimization (PSO) algorithms, we propose a binary learning differential evolution (BLDE) algorithm that can efficiently locate the global optimal solutions by learning from the last population. Then, we theoretically prove the global convergence of BLDE, and compare it with some existing binary-coded evolutionary algorithms (EAs) via numerica","authors_text":"Weicheng Xie, Xiufen Zou, Yu Chen","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2014-01-06T15:54:16Z","title":"A binary differential evolution algorithm learning from explored solutions"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1401.1124","kind":"arxiv","version":2},"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":"sha256:4dafa3cab1fcdbc8d6498c755ac87df04080009573f1afea08842984cbea3f97","target":"record","created_at":"2026-05-18T02:52:06Z","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":"46a2fdaf33bcad7f556c5d64145c71b076919e341bc4f9229c983e0930070fda","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2014-01-06T15:54:16Z","title_canon_sha256":"6bc451d44f4ca8e5bab0ff7dbddcdb2889ef498be7e2d1b48477dd1a8b578e24"},"schema_version":"1.0","source":{"id":"1401.1124","kind":"arxiv","version":2}},"canonical_sha256":"0738597e1a7a9d4c7cfc057a2c8d6cc62dd789b68e841589f8eb114dacccb5eb","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0738597e1a7a9d4c7cfc057a2c8d6cc62dd789b68e841589f8eb114dacccb5eb","first_computed_at":"2026-05-18T02:52:06.220471Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:52:06.220471Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"8RMGqkpW+0Dxs4M72vd/kAZDzbY8HBUzNh8wKaOytby/BevgE2ZZ0/SCo1VAx380uyatw+4mnn7mWbgar9pQAw==","signature_status":"signed_v1","signed_at":"2026-05-18T02:52:06.221078Z","signed_message":"canonical_sha256_bytes"},"source_id":"1401.1124","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4dafa3cab1fcdbc8d6498c755ac87df04080009573f1afea08842984cbea3f97","sha256:4280fcb821d706b41f233304c38cacb81893db3eea523be0ae3abe5e70aae904"],"state_sha256":"44c9ae14413ee09376d8f20a9a6571b10c9c3f7d1962a6f7e55af4035a0fc20e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EeiAKQGRfls9lShrLGjz3ojSDXcJgnQUVRxvVlCaoL6gmOxhXTrujeV8001s7r5rtHw83eDNmpX1zhgRY3NsCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-09T06:52:04.590465Z","bundle_sha256":"3aedf03982da4efad2e6dd3781200c0de42675566636d2440f7cf50f7798dc85"}}