{"id":"https://openalex.org/W4308090300","doi":"https://doi.org/10.1109/hpec55821.2022.9926363","title":"A Multi-GPU Parallel Genetic Algorithm For Large-Scale Vehicle Routing Problems","display_name":"A Multi-GPU Parallel Genetic Algorithm For Large-Scale Vehicle Routing Problems","publication_year":2022,"publication_date":"2022-09-19","ids":{"openalex":"https://openalex.org/W4308090300","doi":"https://doi.org/10.1109/hpec55821.2022.9926363"},"language":"en","primary_location":{"id":"doi:10.1109/hpec55821.2022.9926363","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hpec55821.2022.9926363","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE High Performance Extreme Computing Conference (HPEC)","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/A5076314302","display_name":"Marwan Abdelatti","orcid":"https://orcid.org/0000-0002-4782-6286"},"institutions":[{"id":"https://openalex.org/I17626003","display_name":"University of Rhode Island","ror":"https://ror.org/013ckk937","country_code":"US","type":"education","lineage":["https://openalex.org/I17626003"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Marwan Abdelatti","raw_affiliation_strings":["The University of Rhode Island,Industrial & Mechanical Engineering,Kingston,RI,USA"],"affiliations":[{"raw_affiliation_string":"The University of Rhode Island,Industrial & Mechanical Engineering,Kingston,RI,USA","institution_ids":["https://openalex.org/I17626003"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027496864","display_name":"Manbir Sodhi","orcid":"https://orcid.org/0000-0003-2666-2339"},"institutions":[{"id":"https://openalex.org/I17626003","display_name":"University of Rhode Island","ror":"https://ror.org/013ckk937","country_code":"US","type":"education","lineage":["https://openalex.org/I17626003"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Manbir Sodhi","raw_affiliation_strings":["The University of Rhode Island,Industrial & Mechanical Engineering,Kingston,RI,USA"],"affiliations":[{"raw_affiliation_string":"The University of Rhode Island,Industrial & Mechanical Engineering,Kingston,RI,USA","institution_ids":["https://openalex.org/I17626003"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059940589","display_name":"Resit Sendag","orcid":"https://orcid.org/0000-0002-6922-3363"},"institutions":[{"id":"https://openalex.org/I17626003","display_name":"University of Rhode Island","ror":"https://ror.org/013ckk937","country_code":"US","type":"education","lineage":["https://openalex.org/I17626003"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Resit Sendag","raw_affiliation_strings":["The University of Rhode Island,Industrial & Mechanical Engineering,Kingston,RI,USA"],"affiliations":[{"raw_affiliation_string":"The University of Rhode Island,Industrial & Mechanical Engineering,Kingston,RI,USA","institution_ids":["https://openalex.org/I17626003"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5076314302"],"corresponding_institution_ids":["https://openalex.org/I17626003"],"apc_list":null,"apc_paid":null,"fwci":0.8003,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.76816312,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10567","display_name":"Vehicle Routing Optimization Methods","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9976000189781189,"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/T12176","display_name":"Optimization and Packing Problems","score":0.9958000183105469,"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/parallel-computing","display_name":"Parallel computing","score":0.8157893419265747},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8051096200942993},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6785846948623657},{"id":"https://openalex.org/keywords/vehicle-routing-problem","display_name":"Vehicle routing problem","score":0.4947023093700409},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.46635639667510986},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.4569052755832672},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.43355000019073486},{"id":"https://openalex.org/keywords/parallel-algorithm","display_name":"Parallel algorithm","score":0.42512479424476624},{"id":"https://openalex.org/keywords/throughput","display_name":"Throughput","score":0.4165036678314209},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.4124968945980072},{"id":"https://openalex.org/keywords/routing","display_name":"Routing (electronic design automation)","score":0.38938236236572266},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.11244788765907288},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10686340928077698},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.077534019947052}],"concepts":[{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.8157893419265747},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8051096200942993},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6785846948623657},{"id":"https://openalex.org/C123784306","wikidata":"https://www.wikidata.org/wiki/Q944041","display_name":"Vehicle routing problem","level":3,"score":0.4947023093700409},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46635639667510986},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.4569052755832672},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.43355000019073486},{"id":"https://openalex.org/C120373497","wikidata":"https://www.wikidata.org/wiki/Q1087987","display_name":"Parallel algorithm","level":2,"score":0.42512479424476624},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.4165036678314209},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.4124968945980072},{"id":"https://openalex.org/C74172769","wikidata":"https://www.wikidata.org/wiki/Q1446839","display_name":"Routing (electronic design automation)","level":2,"score":0.38938236236572266},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.11244788765907288},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10686340928077698},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.077534019947052},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/hpec55821.2022.9926363","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hpec55821.2022.9926363","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE High Performance Extreme Computing Conference (HPEC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W164384110","https://openalex.org/W656663116","https://openalex.org/W1526684662","https://openalex.org/W1601649239","https://openalex.org/W1967822105","https://openalex.org/W1978186990","https://openalex.org/W1981456160","https://openalex.org/W1989063768","https://openalex.org/W1993257498","https://openalex.org/W2008146930","https://openalex.org/W2012298530","https://openalex.org/W2026023516","https://openalex.org/W2031103608","https://openalex.org/W2037119827","https://openalex.org/W2041805565","https://openalex.org/W2047047906","https://openalex.org/W2081230102","https://openalex.org/W2108536179","https://openalex.org/W2111174053","https://openalex.org/W2111581650","https://openalex.org/W2118037331","https://openalex.org/W2126105956","https://openalex.org/W2130928692","https://openalex.org/W2325535142","https://openalex.org/W2388422079","https://openalex.org/W2509755532","https://openalex.org/W2555469813","https://openalex.org/W2588104858","https://openalex.org/W2610983883","https://openalex.org/W2690133205","https://openalex.org/W2767033284","https://openalex.org/W2806410342","https://openalex.org/W2807833079","https://openalex.org/W2900562156","https://openalex.org/W2909002869","https://openalex.org/W2913091258","https://openalex.org/W2913205451","https://openalex.org/W2921712036","https://openalex.org/W2979015021","https://openalex.org/W3038899990","https://openalex.org/W3080565011","https://openalex.org/W3131607724","https://openalex.org/W3161432682","https://openalex.org/W3180616925","https://openalex.org/W3182982153","https://openalex.org/W4225745299","https://openalex.org/W4301499553","https://openalex.org/W6601312733","https://openalex.org/W6628893847","https://openalex.org/W6633992998","https://openalex.org/W6677827196","https://openalex.org/W6752994612","https://openalex.org/W6795249852"],"related_works":["https://openalex.org/W4312143452","https://openalex.org/W2018691209","https://openalex.org/W4247364272","https://openalex.org/W3133151256","https://openalex.org/W2132920749","https://openalex.org/W2101108574","https://openalex.org/W2157331354","https://openalex.org/W2626773395","https://openalex.org/W3131953714","https://openalex.org/W1575940985"],"abstract_inverted_index":{"The":[0,62,118],"Vehicle":[1],"Routing":[2],"Problem":[3],"(VRP)":[4],"is":[5,20,64,74,143],"fundamental":[6],"to":[7,16,29,41,50,84,102,135],"logistics":[8],"operations.":[9],"Finding":[10],"optimal":[11],"solutions":[12,32],"for":[13,33,57,91,155],"VRPs":[14,37],"related":[15],"large,":[17],"real-world":[18],"operations":[19],"computationally":[21],"expensive.":[22],"Genetic":[23],"algorithms":[24],"(GA)":[25],"have":[26],"been":[27],"used":[28],"find":[30],"good":[31],"different":[34,111],"types":[35],"of":[36,100,151,166],"but":[38],"are":[39,138],"slow":[40],"converge.":[42],"This":[43],"work":[44],"utilizes":[45],"high-performance":[46],"computing":[47],"(HPC)":[48],"platforms":[49],"design":[51],"a":[52,115,149],"parallel":[53],"GA":[54],"(PGA)":[55],"algorithm":[56,63,79,107,120],"solving":[58],"large-scale":[59],"VRP":[60,97],"problems.":[61],"implemented":[65],"on":[66],"an":[67],"eight-GPU":[68],"NVIDIA":[69],"DGX-l":[70],"server.":[71],"Maximum":[72],"parallelism":[73],"achieved":[75],"by":[76,148],"mapping":[77],"all":[78],"arrays":[80],"into":[81],"block":[82],"threads":[83],"achieve":[85],"high":[86],"throughput":[87],"and":[88,114,153],"reduced":[89,144],"latency":[90],"full":[92],"GPU":[93,112],"utilization.":[94],"Tests":[95],"with":[96,110,163],"benchmark":[98],"problems":[99],"up":[101,134],"20,000":[103,136],"nodes":[104,137],"compare":[105],"the":[106,122,146,156,159,164],"performance":[108,160],"(speed)":[109],"counts":[113],"multi-CPU":[116],"implementation.":[117],"developed":[119],"provides":[121],"following":[123],"improvements":[124],"over":[125,145],"CPU":[126,147],"or":[127],"single-GPU-based":[128],"algorithms:":[129],"(i)":[130],"larger":[131],"problem":[132],"sizes":[133],"handled,":[139],"(ii)":[140],"execution":[141],"time":[142],"factor":[150],"1,700,":[152],"iii)":[154],"range":[157],"tested,":[158],"increases":[161],"monotonically":[162],"number":[165],"GPUs.":[167]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}