{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:YKITBTTMP2K746LPJK4XRIPPR7","short_pith_number":"pith:YKITBTTM","schema_version":"1.0","canonical_sha256":"c29130ce6c7e95fe796f4ab978a1ef8fe0d624b945ef7d500b34c43958c54a34","source":{"kind":"arxiv","id":"1712.01126","version":1},"attestation_state":"computed","paper":{"title":"Optimizing Electric Taxi Charging System: A Data-Driven Approach from Transport Energy Supply Chain Perspective","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.OC"],"primary_cat":"cs.SY","authors_text":"Huimiao Chen, Yide Zhao, Yinghao Jia, Yu Xin, Ziyang Guo","submitted_at":"2017-12-04T14:56:32Z","abstract_excerpt":"In the last decade, the development of electric taxis has motivated rapidly growing research interest in efficiently allocating electric charging stations in the academic literature. To address the driving pattern of electric taxis, we introduce the perspective of transport energy supply chain to capture the charging demand and to transform the charging station allocation problem to a location problem. Based on the P-median and the Min-max models, we developed a data-driven method to evaluate the system efficiency and service quality. We also conduct a case study using GPS trajectory data in B"},"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":"1712.01126","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SY","submitted_at":"2017-12-04T14:56:32Z","cross_cats_sorted":["math.OC"],"title_canon_sha256":"e7cb2480b48e6c824d790310b51c78f1a6cb6b037ecb7d9b2588b9326e54c53b","abstract_canon_sha256":"009ee62464a4f9e95b0733319ecae1a91d72cac25736c76b8e27c146cca2cb7e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:28:59.448737Z","signature_b64":"z6nXmp8qwOXs3ZZqVhCBcwZKtjGeL6xE7sSIMMhqIIPU0bf4luvEXG4DFDEgrbBK9N58hCcBuf7X2Bq78qNZDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c29130ce6c7e95fe796f4ab978a1ef8fe0d624b945ef7d500b34c43958c54a34","last_reissued_at":"2026-05-18T00:28:59.448356Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:28:59.448356Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Optimizing Electric Taxi Charging System: A Data-Driven Approach from Transport Energy Supply Chain Perspective","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.OC"],"primary_cat":"cs.SY","authors_text":"Huimiao Chen, Yide Zhao, Yinghao Jia, Yu Xin, Ziyang Guo","submitted_at":"2017-12-04T14:56:32Z","abstract_excerpt":"In the last decade, the development of electric taxis has motivated rapidly growing research interest in efficiently allocating electric charging stations in the academic literature. To address the driving pattern of electric taxis, we introduce the perspective of transport energy supply chain to capture the charging demand and to transform the charging station allocation problem to a location problem. Based on the P-median and the Min-max models, we developed a data-driven method to evaluate the system efficiency and service quality. We also conduct a case study using GPS trajectory data in B"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1712.01126","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1712.01126","created_at":"2026-05-18T00:28:59.448409+00:00"},{"alias_kind":"arxiv_version","alias_value":"1712.01126v1","created_at":"2026-05-18T00:28:59.448409+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1712.01126","created_at":"2026-05-18T00:28:59.448409+00:00"},{"alias_kind":"pith_short_12","alias_value":"YKITBTTMP2K7","created_at":"2026-05-18T12:31:56.362134+00:00"},{"alias_kind":"pith_short_16","alias_value":"YKITBTTMP2K746LP","created_at":"2026-05-18T12:31:56.362134+00:00"},{"alias_kind":"pith_short_8","alias_value":"YKITBTTM","created_at":"2026-05-18T12:31:56.362134+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/YKITBTTMP2K746LPJK4XRIPPR7","json":"https://pith.science/pith/YKITBTTMP2K746LPJK4XRIPPR7.json","graph_json":"https://pith.science/api/pith-number/YKITBTTMP2K746LPJK4XRIPPR7/graph.json","events_json":"https://pith.science/api/pith-number/YKITBTTMP2K746LPJK4XRIPPR7/events.json","paper":"https://pith.science/paper/YKITBTTM"},"agent_actions":{"view_html":"https://pith.science/pith/YKITBTTMP2K746LPJK4XRIPPR7","download_json":"https://pith.science/pith/YKITBTTMP2K746LPJK4XRIPPR7.json","view_paper":"https://pith.science/paper/YKITBTTM","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1712.01126&json=true","fetch_graph":"https://pith.science/api/pith-number/YKITBTTMP2K746LPJK4XRIPPR7/graph.json","fetch_events":"https://pith.science/api/pith-number/YKITBTTMP2K746LPJK4XRIPPR7/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/YKITBTTMP2K746LPJK4XRIPPR7/action/timestamp_anchor","attest_storage":"https://pith.science/pith/YKITBTTMP2K746LPJK4XRIPPR7/action/storage_attestation","attest_author":"https://pith.science/pith/YKITBTTMP2K746LPJK4XRIPPR7/action/author_attestation","sign_citation":"https://pith.science/pith/YKITBTTMP2K746LPJK4XRIPPR7/action/citation_signature","submit_replication":"https://pith.science/pith/YKITBTTMP2K746LPJK4XRIPPR7/action/replication_record"}},"created_at":"2026-05-18T00:28:59.448409+00:00","updated_at":"2026-05-18T00:28:59.448409+00:00"}