{"id":"https://openalex.org/W2587845379","doi":"https://doi.org/10.1109/liss.2016.7854420","title":"A two-phase greedy strategy in one to many PDVRP","display_name":"A two-phase greedy strategy in one to many PDVRP","publication_year":2016,"publication_date":"2016-07-01","ids":{"openalex":"https://openalex.org/W2587845379","doi":"https://doi.org/10.1109/liss.2016.7854420","mag":"2587845379"},"language":"en","primary_location":{"id":"doi:10.1109/liss.2016.7854420","is_oa":false,"landing_page_url":"https://doi.org/10.1109/liss.2016.7854420","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Conference on Logistics, Informatics and Service Sciences (LISS)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5026815742","display_name":"Jianing Min","orcid":null},"institutions":[{"id":"https://openalex.org/I4210154710","display_name":"Wuxi Taihu Hospital","ror":"https://ror.org/05qp6pd10","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210154710"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianing Min","raw_affiliation_strings":["School of Business, Taihu University of Wuxi, Wuxi, Jiangsu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Business, Taihu University of Wuxi, Wuxi, Jiangsu, China","institution_ids":["https://openalex.org/I4210154710"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113456828","display_name":"Cheng Jin","orcid":"https://orcid.org/0000-0001-7737-5781"},"institutions":[{"id":"https://openalex.org/I4210154710","display_name":"Wuxi Taihu Hospital","ror":"https://ror.org/05qp6pd10","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210154710"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng Jin","raw_affiliation_strings":["School of Business, Taihu University of Wuxi, Wuxi, Jiangsu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Business, Taihu University of Wuxi, Wuxi, Jiangsu, China","institution_ids":["https://openalex.org/I4210154710"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210154710"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"28","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10567","display_name":"Vehicle Routing Optimization Methods","score":0.9950000047683716,"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"}},"topics":[{"id":"https://openalex.org/T10567","display_name":"Vehicle Routing Optimization Methods","score":0.9950000047683716,"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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9940999746322632,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11814","display_name":"Advanced Manufacturing and Logistics Optimization","score":0.9829000234603882,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/pickup","display_name":"Pickup","score":0.7359709143638611},{"id":"https://openalex.org/keywords/routing","display_name":"Routing (electronic design automation)","score":0.71388179063797},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6992574334144592},{"id":"https://openalex.org/keywords/vehicle-routing-problem","display_name":"Vehicle routing problem","score":0.6856743097305298},{"id":"https://openalex.org/keywords/greedy-algorithm","display_name":"Greedy algorithm","score":0.6566038727760315},{"id":"https://openalex.org/keywords/schedule","display_name":"Schedule","score":0.5970511436462402},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5797231793403625},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5529068112373352},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.49369582533836365},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4769688546657562},{"id":"https://openalex.org/keywords/phase","display_name":"Phase (matter)","score":0.46900129318237305},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.41550323367118835},{"id":"https://openalex.org/keywords/operations-research","display_name":"Operations research","score":0.36044663190841675},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.22028988599777222},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16159191727638245},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.14302244782447815},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.1404387652873993},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.13414239883422852}],"concepts":[{"id":"https://openalex.org/C2776221269","wikidata":"https://www.wikidata.org/wiki/Q572648","display_name":"Pickup","level":3,"score":0.7359709143638611},{"id":"https://openalex.org/C74172769","wikidata":"https://www.wikidata.org/wiki/Q1446839","display_name":"Routing (electronic design automation)","level":2,"score":0.71388179063797},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6992574334144592},{"id":"https://openalex.org/C123784306","wikidata":"https://www.wikidata.org/wiki/Q944041","display_name":"Vehicle routing problem","level":3,"score":0.6856743097305298},{"id":"https://openalex.org/C51823790","wikidata":"https://www.wikidata.org/wiki/Q504353","display_name":"Greedy algorithm","level":2,"score":0.6566038727760315},{"id":"https://openalex.org/C68387754","wikidata":"https://www.wikidata.org/wiki/Q7271585","display_name":"Schedule","level":2,"score":0.5970511436462402},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5797231793403625},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5529068112373352},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.49369582533836365},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4769688546657562},{"id":"https://openalex.org/C44280652","wikidata":"https://www.wikidata.org/wiki/Q104837","display_name":"Phase (matter)","level":2,"score":0.46900129318237305},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.41550323367118835},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.36044663190841675},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.22028988599777222},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16159191727638245},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.14302244782447815},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.1404387652873993},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.13414239883422852},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/liss.2016.7854420","is_oa":false,"landing_page_url":"https://doi.org/10.1109/liss.2016.7854420","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Conference on Logistics, Informatics and Service Sciences (LISS)","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":9,"referenced_works":["https://openalex.org/W1967052903","https://openalex.org/W2019567064","https://openalex.org/W2061233155","https://openalex.org/W2063659595","https://openalex.org/W2119650324","https://openalex.org/W2119673940","https://openalex.org/W2349199048","https://openalex.org/W2372648622","https://openalex.org/W2376071377"],"related_works":["https://openalex.org/W3183948672","https://openalex.org/W2741596907","https://openalex.org/W4248894450","https://openalex.org/W4293253022","https://openalex.org/W2183192769","https://openalex.org/W2048314949","https://openalex.org/W3204694157","https://openalex.org/W2809387092","https://openalex.org/W3119129187","https://openalex.org/W4213402591"],"abstract_inverted_index":{"The":[0,63,86,109],"extension":[1],"class":[2],"of":[3,66],"the":[4,42,72,76,83,93,102,135],"traditional":[5],"vehicle":[6,39,60,98],"routing":[7,61,65,77],"problem,":[8],"where":[9],"there":[10],"are":[11,20],"several":[12],"tasks":[13,79],"in":[14,30,35,71,82,129],"a":[15,67],"goods":[16,19],"transportation":[17],"and":[18,58,75,96,100,105,119,121,131],"transported":[21],"from":[22],"one":[23,54],"pickup":[24,57],"point":[25],"to":[26,37,55],"many":[27,56],"delivery":[28,59],"points":[29],"each":[31],"task,":[32],"is":[33,117],"studied":[34],"order":[36],"schedule":[38],"routes":[40],"with":[41,101],"lowest":[43],"cost.":[44],"A":[45],"two-phase":[46,114],"greedy":[47,115],"strategy":[48,116],"was":[49,69,80,89],"put":[50],"forward":[51],"based":[52],"on":[53],"problem.":[62],"inner":[64],"task":[68],"established":[70],"first":[73],"phase,":[74],"between":[78],"scheduled":[81],"second":[84],"phase.":[85],"mathematical":[87],"model":[88],"set":[90],"up":[91],"under":[92],"single":[94],"depot":[95],"sole":[97],"model,":[99],"mileage":[103,130],"limit":[104],"time":[106],"window":[107],"constraints.":[108],"experiment":[110],"results":[111,128],"show":[112],"that":[113],"feasible":[118],"effective":[120],"also":[122],"it":[123],"can":[124],"get":[125],"better":[126],"optimal":[127],"cost":[132],"saving":[133],"than":[134],"improved":[136],"clarke-wright":[137],"algorithm.":[138]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}