{"id":"https://openalex.org/W2967941995","doi":"https://doi.org/10.1109/cec.2019.8790018","title":"A Multi-Start Iterated Local Search Algorithm for the Maximum Scatter Traveling Salesman Problem","display_name":"A Multi-Start Iterated Local Search Algorithm for the Maximum Scatter Traveling Salesman Problem","publication_year":2019,"publication_date":"2019-06-01","ids":{"openalex":"https://openalex.org/W2967941995","doi":"https://doi.org/10.1109/cec.2019.8790018","mag":"2967941995"},"language":"en","primary_location":{"id":"doi:10.1109/cec.2019.8790018","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec.2019.8790018","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Congress on Evolutionary Computation (CEC)","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/A5014082246","display_name":"Venkatesh Pandiri","orcid":"https://orcid.org/0000-0001-5077-5435"},"institutions":[{"id":"https://openalex.org/I36893310","display_name":"University of Hyderabad","ror":"https://ror.org/04a7rxb17","country_code":"IN","type":"education","lineage":["https://openalex.org/I36893310"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Pandiri Venkatesh","raw_affiliation_strings":["School of Computer & Information Sciences, University of Hyderabad, Hyderabad, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer & Information Sciences, University of Hyderabad, Hyderabad, India","institution_ids":["https://openalex.org/I36893310"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045783983","display_name":"Alok Singh","orcid":"https://orcid.org/0000-0003-3585-4957"},"institutions":[{"id":"https://openalex.org/I36893310","display_name":"University of Hyderabad","ror":"https://ror.org/04a7rxb17","country_code":"IN","type":"education","lineage":["https://openalex.org/I36893310"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Alok Singh","raw_affiliation_strings":["School of Computer & Information Sciences, University of Hyderabad, Hyderabad, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer & Information Sciences, University of Hyderabad, Hyderabad, India","institution_ids":["https://openalex.org/I36893310"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043565079","display_name":"Rammohan Mallipeddi","orcid":"https://orcid.org/0000-0001-9071-1145"},"institutions":[{"id":"https://openalex.org/I31419693","display_name":"Kyungpook National University","ror":"https://ror.org/040c17130","country_code":"KR","type":"education","lineage":["https://openalex.org/I31419693"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Rammohan Mallipeddi","raw_affiliation_strings":["School of Electronics Engineering, Kyungpook National University, Daegu, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronics Engineering, Kyungpook National University, Daegu, Republic of Korea","institution_ids":["https://openalex.org/I31419693"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.8583,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.9072738,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1390","last_page":"1397"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10567","display_name":"Vehicle Routing Optimization Methods","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9980000257492065,"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":0.9904999732971191,"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/travelling-salesman-problem","display_name":"Travelling salesman problem","score":0.9296287894248962},{"id":"https://openalex.org/keywords/iterated-local-search","display_name":"Iterated local search","score":0.7944871187210083},{"id":"https://openalex.org/keywords/2-opt","display_name":"2-opt","score":0.6978378295898438},{"id":"https://openalex.org/keywords/iterated-function","display_name":"Iterated function","score":0.6660043597221375},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6444445252418518},{"id":"https://openalex.org/keywords/hamiltonian-path","display_name":"Hamiltonian path","score":0.6100835204124451},{"id":"https://openalex.org/keywords/bottleneck-traveling-salesman-problem","display_name":"Bottleneck traveling salesman problem","score":0.6078475713729858},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5383369326591492},{"id":"https://openalex.org/keywords/local-search","display_name":"Local search (optimization)","score":0.5335859060287476},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5298469066619873},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5286864638328552},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5246096849441528},{"id":"https://openalex.org/keywords/traveling-purchaser-problem","display_name":"Traveling purchaser problem","score":0.4230906665325165},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.37017449736595154},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.19498217105865479}],"concepts":[{"id":"https://openalex.org/C175859090","wikidata":"https://www.wikidata.org/wiki/Q322212","display_name":"Travelling salesman problem","level":2,"score":0.9296287894248962},{"id":"https://openalex.org/C124145224","wikidata":"https://www.wikidata.org/wiki/Q6094397","display_name":"Iterated local search","level":3,"score":0.7944871187210083},{"id":"https://openalex.org/C106472803","wikidata":"https://www.wikidata.org/wiki/Q291440","display_name":"2-opt","level":3,"score":0.6978378295898438},{"id":"https://openalex.org/C140479938","wikidata":"https://www.wikidata.org/wiki/Q5254619","display_name":"Iterated function","level":2,"score":0.6660043597221375},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6444445252418518},{"id":"https://openalex.org/C86524685","wikidata":"https://www.wikidata.org/wiki/Q273037","display_name":"Hamiltonian path","level":3,"score":0.6100835204124451},{"id":"https://openalex.org/C7668213","wikidata":"https://www.wikidata.org/wiki/Q4949085","display_name":"Bottleneck traveling salesman problem","level":3,"score":0.6078475713729858},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5383369326591492},{"id":"https://openalex.org/C135320971","wikidata":"https://www.wikidata.org/wiki/Q1868524","display_name":"Local search (optimization)","level":2,"score":0.5335859060287476},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5298469066619873},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5286864638328552},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5246096849441528},{"id":"https://openalex.org/C4331618","wikidata":"https://www.wikidata.org/wiki/Q7836034","display_name":"Traveling purchaser problem","level":4,"score":0.4230906665325165},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.37017449736595154},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.19498217105865479},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cec.2019.8790018","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec.2019.8790018","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Congress on Evolutionary Computation (CEC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.49000000953674316,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1502125971","https://openalex.org/W1571087346","https://openalex.org/W1970940354","https://openalex.org/W1995719137","https://openalex.org/W2004464961","https://openalex.org/W2004512957","https://openalex.org/W2007907580","https://openalex.org/W2037938479","https://openalex.org/W2085110997","https://openalex.org/W2160218441","https://openalex.org/W2168155808","https://openalex.org/W2174834537","https://openalex.org/W2177140748","https://openalex.org/W2183207849","https://openalex.org/W2324108981","https://openalex.org/W2471508234","https://openalex.org/W2590847231","https://openalex.org/W2789080728","https://openalex.org/W2804079469","https://openalex.org/W2888310444","https://openalex.org/W2964294288","https://openalex.org/W3009009611","https://openalex.org/W3204855000","https://openalex.org/W4231343630","https://openalex.org/W6683584131","https://openalex.org/W6720025408","https://openalex.org/W6748583387"],"related_works":["https://openalex.org/W4389782626","https://openalex.org/W4376138746","https://openalex.org/W2359992618","https://openalex.org/W2361554335","https://openalex.org/W4220987199","https://openalex.org/W2362402143","https://openalex.org/W3112607009","https://openalex.org/W4321062523","https://openalex.org/W2259723333","https://openalex.org/W1002323541"],"abstract_inverted_index":{"The":[0,38],"maximum":[1],"scatter":[2],"traveling":[3,13],"salesman":[4,14],"problem":[5,15],"(MSTSP)":[6],"is":[7,20],"a":[8,23,27,53],"variant":[9],"of":[10,78,85,105],"the":[11,18,31,60,83,86,92,103,106],"well-known":[12],"(TSP)":[16],"where":[17],"objective":[19],"to":[21],"find":[22],"Hamiltonian":[24],"cycle":[25],"on":[26,67],"graph":[28],"that":[29],"maximizes":[30],"minimum":[32],"length":[33],"among":[34],"its":[35],"constituent":[36],"edges.":[37],"MSTSP":[39],"finds":[40],"important":[41],"application":[42],"in":[43],"manufacturing":[44],"and":[45,69,99],"medical":[46],"imaging.":[47],"In":[48],"this":[49],"study,":[50],"we":[51],"propose":[52],"multi-start":[54],"iterated":[55],"local":[56,63],"search":[57,64],"algorithm":[58],"for":[59],"MSTSP.":[61],"Two":[62],"algorithms":[65],"based":[66],"insertion":[68],"modified":[70],"2-opt":[71],"moves":[72],"have":[73],"been":[74],"developed":[75],"as":[76],"part":[77],"our":[79],"approach.":[80,108],"To":[81],"investigate":[82],"performance":[84],"proposed":[87,107],"approach,":[88],"benchmark":[89],"instances":[90],"from":[91],"standard":[93],"TSPLIB":[94],"are":[95],"used.":[96],"Computational":[97],"results":[98],"their":[100],"analysis":[101],"show":[102],"effectiveness":[104]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
