{"id":"https://openalex.org/W3008569710","doi":"https://doi.org/10.1109/iscmi47871.2019.9004294","title":"Optimising the Vehicle Routing Problem with Time Windows under Standardised Metrics","display_name":"Optimising the Vehicle Routing Problem with Time Windows under Standardised Metrics","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W3008569710","doi":"https://doi.org/10.1109/iscmi47871.2019.9004294","mag":"3008569710"},"language":"en","primary_location":{"id":"doi:10.1109/iscmi47871.2019.9004294","doi":"https://doi.org/10.1109/iscmi47871.2019.9004294","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscmi47871.2019.9004294","pdf_url":null,"source":{"id":"https://openalex.org/S7407086718","display_name":"International Conference on Soft Computing & Machine Intelligence (ISCMI)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 6th International Conference on Soft Computing & Machine Intelligence (ISCMI)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5008736197","display_name":"Krupa Prag","orcid":"https://orcid.org/0000-0002-4821-8151","observed_orcids":["https://orcid.org/0000-0002-4821-8151"]},"institutions":[{"id":"https://openalex.org/I192619145","display_name":"University of the Witwatersrand","ror":"https://ror.org/03rp50x72","country_code":"ZA","type":"education","lineage":["https://openalex.org/I192619145"]}],"countries":["ZA"],"is_corresponding":false,"raw_author_name":"Krupa Prag","raw_affiliation_strings":["CSAM, University of the Witwatersrand, Johannesburg, South Africa"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CSAM, University of the Witwatersrand, Johannesburg, South Africa","institution_ids":["https://openalex.org/I192619145"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015475693","display_name":"Matthew Woolway","orcid":"https://orcid.org/0000-0002-4902-851X","observed_orcids":["https://orcid.org/0000-0002-4902-851X"]},"institutions":[{"id":"https://openalex.org/I192619145","display_name":"University of the Witwatersrand","ror":"https://ror.org/03rp50x72","country_code":"ZA","type":"education","lineage":["https://openalex.org/I192619145"]}],"countries":["ZA"],"is_corresponding":false,"raw_author_name":"Matthew Woolway","raw_affiliation_strings":["CSAM, University of the Witwatersrand, Wits Institute of Data Science, Johannesburg, South Africa"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CSAM, University of the Witwatersrand, Wits Institute of Data Science, Johannesburg, South Africa","institution_ids":["https://openalex.org/I192619145"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055295888","display_name":"Byron Alexander Jacobs","orcid":"https://orcid.org/0000-0002-3121-3565","observed_orcids":["https://orcid.org/0000-0002-3121-3565"]},"institutions":[{"id":"https://openalex.org/I192619145","display_name":"University of the Witwatersrand","ror":"https://ror.org/03rp50x72","country_code":"ZA","type":"education","lineage":["https://openalex.org/I192619145"]},{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU","ZA"],"is_corresponding":false,"raw_author_name":"Byron A. Jacobs","raw_affiliation_strings":["CSAM, University of the Witwatersrand Maths & Stats, UNSW Australia, Johannesburg, South Africa"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CSAM, University of the Witwatersrand Maths & Stats, UNSW Australia, Johannesburg, South Africa","institution_ids":["https://openalex.org/I192619145","https://openalex.org/I31746571"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":93},"biblio":{"volume":"1","issue":null,"first_page":"111","last_page":"115"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10567","display_name":"Vehicle Routing Optimization Methods","score":1.0,"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":1.0,"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.0,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12306","display_name":"Urban and Freight Transport Logistics","score":0.0,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/vehicle-routing-problem-with-time-windows","display_name":"vehicle routing problem with time windows","score":0.9869999885559082},{"id":"https://openalex.org/keywords/metaheuristic-optimization","display_name":"metaheuristic optimization","score":0.8009999990463257},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"genetic algorithm","score":0.9509999752044678},{"id":"https://openalex.org/keywords/particle-swarm-optimization","display_name":"particle swarm optimization","score":0.9959999918937683},{"id":"https://openalex.org/keywords/performance-indicators","display_name":"performance indicators","score":0.5899999737739563},{"id":"https://openalex.org/keywords/benchmark-comparison","display_name":"benchmark comparison","score":0.6129999756813049},{"id":"https://openalex.org/keywords/solution-quality","display_name":"solution quality","score":0.6740000247955322},{"id":"https://openalex.org/keywords/cpu-time","display_name":"CPU time","score":0.7269999980926514},{"id":"https://openalex.org/keywords/combinatorial-optimization","display_name":"combinatorial optimization","score":0.9319999814033508}],"concepts":[{"id":"https://openalex.org/C123784306","wikidata":"https://www.wikidata.org/wiki/Q944041","display_name":"Vehicle routing problem","level":3,"score":0.8657889366149902},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.859160840511322},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.8574318885803223},{"id":"https://openalex.org/C109718341","wikidata":"https://www.wikidata.org/wiki/Q1385229","display_name":"Metaheuristic","level":2,"score":0.6810138821601868},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.6496901512145996},{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.5908463001251221},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5777880549430847},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.5176380276679993},{"id":"https://openalex.org/C74172769","wikidata":"https://www.wikidata.org/wiki/Q1446839","display_name":"Routing (electronic design automation)","level":2,"score":0.39622145891189575},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36279788613319397},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2978348135948181},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07710877060890198},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iscmi47871.2019.9004294","doi":"https://doi.org/10.1109/iscmi47871.2019.9004294","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscmi47871.2019.9004294","pdf_url":null,"source":{"id":"https://openalex.org/S7407086718","display_name":"International Conference on Soft Computing & Machine Intelligence (ISCMI)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 6th International Conference on Soft Computing & Machine Intelligence (ISCMI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2007423183","https://openalex.org/W2018691209","https://openalex.org/W2066086285","https://openalex.org/W2070637511","https://openalex.org/W2096305430","https://openalex.org/W2104670598","https://openalex.org/W2115963027","https://openalex.org/W2116675171","https://openalex.org/W2131613989","https://openalex.org/W2224737250","https://openalex.org/W4246598646"],"related_works":["https://openalex.org/W94181061","https://openalex.org/W2186983469","https://openalex.org/W2469598054","https://openalex.org/W2116675171","https://openalex.org/W4408861971","https://openalex.org/W2206826855","https://openalex.org/W2793504099","https://openalex.org/W7097527222","https://openalex.org/W4379539425","https://openalex.org/W1975501199"],"abstract_inverted_index":{"The":[0,113,205,227],"Vehicle":[1],"Routing":[2],"Problem":[3,14],"with":[4,223],"Time":[5],"Windows":[6],"(VRPTW)":[7],"is":[8,175,182],"an":[9],"established":[10],"NP-hard":[11],"Combinatorial":[12],"Optimisation":[13,101],"(COP).":[15],"While":[16],"much":[17],"research":[18],"has":[19,31,42],"been":[20,32,170],"undertaken":[21],"in":[22,89,235],"developing":[23],"solution":[24,181,228],"mechanisms":[25],"to":[26,44,57,60,78,135,138,166,240],"the":[27,40,52,61,68,71,90,122,125,131,139,151,173,178,184,187,191,194,199,202,209,213,217,224,241,244],"VRPTW,":[28],"this":[29],"work":[30,38,76],"developed":[33],"without":[34],"comparative":[35,143],"metrics.":[36],"Previous":[37],"on":[39,108,150],"VRPTW":[41,62,242],"failed":[43],"provide":[45],"both":[46],"a":[47,80,109],"comprehensive":[48],"computational":[49,142],"review":[50,144],"comparing":[51],"performance":[53],"of":[54,70,82,124,186,201],"metaheuristics":[55],"applied":[56,94,126,153],"finding":[58],"solutions":[59,137,188,218,239],"under":[63,104],"standardised":[64,106],"experimental":[65],"conditions,":[66],"and":[67,98,116,129,148,155,193,212,230,247],"effects":[69],"employed":[72,156],"metric":[73,127,157,203,231],"schemes.":[74,158,204],"This":[75,141],"aims":[77],"introduce":[79],"means":[81],"comparison":[83],"between":[84],"leading":[85],"metaheuristic":[86],"methods":[87],"found":[88],"literature.":[91],"Conducted":[92],"experiments":[93],"Genetic":[95],"Algorithm":[96],"(GA)":[97],"Particle":[99],"Swarm":[100],"algorithm":[102,246],"(PSO)":[103],"two":[105],"metrics":[107],"well-known":[110],"benchmark":[111,210,225],"dataset.":[112],"results":[114,160,206],"verify":[115],"resemble":[117],"previously":[118],"reported":[119,171],"results,":[120],"question":[121],"design":[123,200],"schemes":[128],"record":[130],"CPU":[132],"time":[133,214],"taken":[134],"obtain":[136],"VRPTW.":[140],"critically":[145],"analyses,":[146],"compares":[147],"comments":[149],"replicated":[152],"techniques":[154],"Significant":[159],"include:":[161],"obtaining":[162],"competitive":[163,222],"timings":[164],"relative":[165],"those":[167],"which":[168,216],"have":[169],"if":[172],"GA":[174,192],"terminated":[176],"when":[177],"best":[179],"known":[180],"met;":[183],"quality":[185],"produced":[189],"by":[190],"PSO":[195,245],"algorithm;":[196],"insight":[197],"into":[198],"obtained":[207,238],"match":[208],"values,":[211],"within":[215],"are":[219,221,243],"computed":[220],"times.":[226],"technique":[229],"scheme":[232],"combination":[233],"which,":[234],"general,":[236],"efficiently":[237],"Metric":[248],"A.":[249]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-10-08T09:06:37.294493","created_date":"2020-03-06T00:00:00"}