{"id":"https://openalex.org/W4390532426","doi":"https://doi.org/10.1145/3632410.3632426","title":"A Learning Approach for Discovering Cost-Efficient Integrated Sourcing and Routing Strategies in E-Commerce","display_name":"A Learning Approach for Discovering Cost-Efficient Integrated Sourcing and Routing Strategies in E-Commerce","publication_year":2024,"publication_date":"2024-01-03","ids":{"openalex":"https://openalex.org/W4390532426","doi":"https://doi.org/10.1145/3632410.3632426"},"language":"en","primary_location":{"id":"doi:10.1145/3632410.3632426","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3632410.3632426","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th Joint International Conference on Data Science & Management of Data (11th ACM IKDD CODS and 29th COMAD)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5068372952","display_name":"Omkar Shelke","orcid":"https://orcid.org/0000-0003-2767-8607"},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Omkar Shelke","raw_affiliation_strings":["TCS Research, India"],"affiliations":[{"raw_affiliation_string":"TCS Research, India","institution_ids":["https://openalex.org/I55215948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067249098","display_name":"Pranavi Pathakota","orcid":"https://orcid.org/0000-0002-2216-3623"},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Pranavi Pathakota","raw_affiliation_strings":["TCS Research, India"],"affiliations":[{"raw_affiliation_string":"TCS Research, India","institution_ids":["https://openalex.org/I55215948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065025560","display_name":"Anandsingh Chauhan","orcid":"https://orcid.org/0009-0007-8639-4029"},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Anandsingh Chauhan","raw_affiliation_strings":["TCS Research, India"],"affiliations":[{"raw_affiliation_string":"TCS Research, India","institution_ids":["https://openalex.org/I55215948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028455101","display_name":"Hardik Meisheri","orcid":"https://orcid.org/0000-0002-9014-1098"},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Hardik Meisheri","raw_affiliation_strings":["TCS Research, India"],"affiliations":[{"raw_affiliation_string":"TCS Research, India","institution_ids":["https://openalex.org/I55215948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045214135","display_name":"Harshad Khadilkar","orcid":"https://orcid.org/0000-0003-3601-778X"},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Harshad Khadilkar","raw_affiliation_strings":["Tata Consultancy Services Ltd, India"],"affiliations":[{"raw_affiliation_string":"Tata Consultancy Services Ltd, India","institution_ids":["https://openalex.org/I55215948"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009374923","display_name":"Balaraman Ravindran","orcid":"https://orcid.org/0000-0002-5364-7639"},"institutions":[{"id":"https://openalex.org/I24676775","display_name":"Indian Institute of Technology Madras","ror":"https://ror.org/03v0r5n49","country_code":"IN","type":"facility","lineage":["https://openalex.org/I24676775"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Balaraman Ravindran","raw_affiliation_strings":["IIT Madras, India"],"affiliations":[{"raw_affiliation_string":"IIT Madras, India","institution_ids":["https://openalex.org/I24676775"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5068372952"],"corresponding_institution_ids":["https://openalex.org/I55215948"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.00298107,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"430","last_page":"438"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11942","display_name":"Transportation and Mobility Innovations","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11942","display_name":"Transportation and Mobility Innovations","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10567","display_name":"Vehicle Routing Optimization Methods","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12306","display_name":"Urban and Freight Transport Logistics","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.781667947769165},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.613324761390686},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5705126523971558},{"id":"https://openalex.org/keywords/routing","display_name":"Routing (electronic design automation)","score":0.5060967803001404},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.4831378161907196},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.45716914534568787},{"id":"https://openalex.org/keywords/operations-research","display_name":"Operations research","score":0.35313016176223755},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.32397258281707764},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3078550696372986},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.14545133709907532}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.781667947769165},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.613324761390686},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5705126523971558},{"id":"https://openalex.org/C74172769","wikidata":"https://www.wikidata.org/wiki/Q1446839","display_name":"Routing (electronic design automation)","level":2,"score":0.5060967803001404},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.4831378161907196},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.45716914534568787},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.35313016176223755},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.32397258281707764},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3078550696372986},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.14545133709907532},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3632410.3632426","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3632410.3632426","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th Joint International Conference on Data Science & Management of Data (11th ACM IKDD CODS and 29th COMAD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1964852969","https://openalex.org/W1977133702","https://openalex.org/W2020931139","https://openalex.org/W2081230102","https://openalex.org/W2090435272","https://openalex.org/W2098156747","https://openalex.org/W2890072063","https://openalex.org/W3087935424","https://openalex.org/W3160021293","https://openalex.org/W3197555620","https://openalex.org/W4206357259","https://openalex.org/W4226237846","https://openalex.org/W4281789008","https://openalex.org/W4313491989","https://openalex.org/W4365800371"],"related_works":["https://openalex.org/W3096874164","https://openalex.org/W2937181779","https://openalex.org/W2386410636","https://openalex.org/W1985560493","https://openalex.org/W2357975469","https://openalex.org/W2145363145","https://openalex.org/W1626977535","https://openalex.org/W4284974072","https://openalex.org/W2341346307","https://openalex.org/W4225269853"],"abstract_inverted_index":{"This":[0,54],"paper":[1],"presents":[2],"an":[3,100,110],"integrated":[4],"algorithmic":[5,205],"framework":[6],"for":[7,66,140,196],"minimising":[8],"product":[9],"delivery":[10],"costs":[11],"in":[12,56,191],"e-commerce":[13],"(known":[14],"as":[15,120,127,162,164,176],"the":[16,22,27,70,92,149,158,165],"cost-to-serve":[17],"or":[18],"CTS).":[19],"One":[20],"of":[21,30,38,46,52,59,62,72,81,84,144],"major":[23],"challenges":[24],"plaguing":[25],"is":[26,174],"large":[28],"volume":[29],"dynamically":[31],"generated":[32],"orders":[33,89],"from":[34,44,91,148],"multiple":[35,88],"customers,":[36],"each":[37,67],"which":[39,85],"has":[40],"to":[41,74],"be":[42],"fulfilled":[43],"one":[45],"several":[47],"warehouses":[48],"using":[49,185],"a":[50,63,75,177,186],"fleet":[51],"vehicles.":[53],"results":[55],"two":[57],"levels":[58],"decision-making:":[60],"selection":[61],"fulfillment":[64,159,197],"node":[65,160,198],"order":[68],"(including":[69],"option":[71],"deferral":[73],"future":[76],"time),":[77],"followed":[78],"by":[79,157,184],"routing":[80,113,166],"vehicles":[82],"(each":[83],"can":[86],"carry":[87],"originating":[90],"same":[93],"warehouse).":[94],"To":[95],"handle":[96],"this,":[97],"we":[98],"propose":[99],"approach":[101],"that":[102,151,203],"combines":[103],"graph":[104],"neural":[105],"networks,":[106],"reinforcement":[107],"learning,":[108],"and":[109,134,168,182],"existing":[111],"vehicle":[112,124],"heuristic.":[114],"We":[115],"include":[116],"real-world":[117],"constraints":[118,136],"such":[119,126],"warehouse":[121],"inventory":[122],"capacity,":[123,133],"characteristics":[125],"travel":[128],"times,":[129,131],"service":[130],"carrying":[132],"customer":[135],"including":[137],"time":[138],"windows":[139],"delivery.":[141],"The":[142,172],"complexity":[143],"this":[145,204],"problem":[146,173],"arises":[147],"fact":[150],"outcomes":[152],"(rewards)":[153],"are":[154,169],"driven":[155],"both":[156],"mapping":[161],"well":[163],"algorithms,":[167],"spatio-temporally":[170],"distributed.":[171],"formulated":[175],"Markov":[178],"Decision":[179],"Process":[180],"(MDP)":[181],"solved":[183],"Graph":[187],"Auto":[188],"Encoder":[189],"(GAE)":[190],"combination":[192],"with":[193],"Deep":[194],"Q-Learning":[195],"mapping.":[199],"Our":[200],"experiments":[201],"show":[202],"pipeline":[206],"outperforms":[207],"pure":[208],"heuristic":[209],"policies.":[210]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}