{"id":"https://openalex.org/W4417300751","doi":"https://doi.org/10.48550/arxiv.2505.12399","title":"Optimizing Interplanetary Trajectories using Hybrid Meta-heuristic","display_name":"Optimizing Interplanetary Trajectories using Hybrid Meta-heuristic","publication_year":2025,"publication_date":"2025-05-18","ids":{"openalex":"https://openalex.org/W4417300751","doi":"https://doi.org/10.48550/arxiv.2505.12399"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2505.12399","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2505.12399","pdf_url":"https://arxiv.org/pdf/2505.12399","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2505.12399","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5013502739","display_name":"Amin Abdollahi Dehkordi","orcid":"https://orcid.org/0000-0002-9753-3035"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dehkordi, Amin Abdollahi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5057442747","display_name":"Mehdi Neshat","orcid":"https://orcid.org/0000-0002-9537-9513"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Neshat, Mehdi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11082","display_name":"Spacecraft Dynamics and Control","score":0.7501999735832214,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T11082","display_name":"Spacecraft Dynamics and Control","score":0.7501999735832214,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T11622","display_name":"Maritime Navigation and Safety","score":0.07779999822378159,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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":0.05990000069141388,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/metaheuristic","display_name":"Metaheuristic","score":0.6219000220298767},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.5418000221252441},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.5349000096321106},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.506600022315979},{"id":"https://openalex.org/keywords/premature-convergence","display_name":"Premature convergence","score":0.46959999203681946},{"id":"https://openalex.org/keywords/aerospace","display_name":"Aerospace","score":0.4675999879837036},{"id":"https://openalex.org/keywords/emulation","display_name":"Emulation","score":0.46399998664855957},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.44510000944137573},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.4244000017642975},{"id":"https://openalex.org/keywords/trajectory-optimization","display_name":"Trajectory optimization","score":0.4178999960422516}],"concepts":[{"id":"https://openalex.org/C109718341","wikidata":"https://www.wikidata.org/wiki/Q1385229","display_name":"Metaheuristic","level":2,"score":0.6219000220298767},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6129999756813049},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5494999885559082},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.5418000221252441},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.5349000096321106},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.506600022315979},{"id":"https://openalex.org/C58758708","wikidata":"https://www.wikidata.org/wiki/Q7240233","display_name":"Premature convergence","level":3,"score":0.46959999203681946},{"id":"https://openalex.org/C167740415","wikidata":"https://www.wikidata.org/wiki/Q2876213","display_name":"Aerospace","level":2,"score":0.4675999879837036},{"id":"https://openalex.org/C149810388","wikidata":"https://www.wikidata.org/wiki/Q5374873","display_name":"Emulation","level":2,"score":0.46399998664855957},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.44510000944137573},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.4244000017642975},{"id":"https://openalex.org/C173246807","wikidata":"https://www.wikidata.org/wiki/Q7833062","display_name":"Trajectory optimization","level":3,"score":0.4178999960422516},{"id":"https://openalex.org/C135320971","wikidata":"https://www.wikidata.org/wiki/Q1868524","display_name":"Local search (optimization)","level":2,"score":0.39480000734329224},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.3637999892234802},{"id":"https://openalex.org/C104060986","wikidata":"https://www.wikidata.org/wiki/Q180046","display_name":"Space exploration","level":2,"score":0.3537999987602234},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.3492000102996826},{"id":"https://openalex.org/C68781425","wikidata":"https://www.wikidata.org/wiki/Q2052203","display_name":"Multi-objective optimization","level":2,"score":0.3273000121116638},{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.3231000006198883},{"id":"https://openalex.org/C193254401","wikidata":"https://www.wikidata.org/wiki/Q2160088","display_name":"Robust optimization","level":2,"score":0.3222000002861023},{"id":"https://openalex.org/C164752517","wikidata":"https://www.wikidata.org/wiki/Q5570875","display_name":"Global optimization","level":2,"score":0.302700012922287},{"id":"https://openalex.org/C141934464","wikidata":"https://www.wikidata.org/wiki/Q3305386","display_name":"Local optimum","level":2,"score":0.296099990606308},{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.2946999967098236},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.2842000126838684},{"id":"https://openalex.org/C74750220","wikidata":"https://www.wikidata.org/wiki/Q2662197","display_name":"Differential evolution","level":2,"score":0.2816999852657318},{"id":"https://openalex.org/C161840515","wikidata":"https://www.wikidata.org/wiki/Q186131","display_name":"Terrain","level":2,"score":0.2809000015258789},{"id":"https://openalex.org/C29829512","wikidata":"https://www.wikidata.org/wiki/Q40218","display_name":"Spacecraft","level":2,"score":0.26649999618530273},{"id":"https://openalex.org/C2987595161","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Optimization algorithm","level":2,"score":0.2655999958515167},{"id":"https://openalex.org/C122357587","wikidata":"https://www.wikidata.org/wiki/Q6934508","display_name":"Multi-swarm optimization","level":3,"score":0.2612999975681305},{"id":"https://openalex.org/C50897621","wikidata":"https://www.wikidata.org/wiki/Q2665508","display_name":"Hybrid system","level":2,"score":0.26100000739097595},{"id":"https://openalex.org/C62469222","wikidata":"https://www.wikidata.org/wiki/Q17092103","display_name":"Hybrid algorithm (constraint satisfaction)","level":5,"score":0.25760000944137573},{"id":"https://openalex.org/C125583679","wikidata":"https://www.wikidata.org/wiki/Q755673","display_name":"Search algorithm","level":2,"score":0.25609999895095825}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2505.12399","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2505.12399","pdf_url":"https://arxiv.org/pdf/2505.12399","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2505.12399","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2505.12399","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2505.12399","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2505.12399","pdf_url":"https://arxiv.org/pdf/2505.12399","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"an":[3,89],"advanced":[4,174],"hybrid":[5,215],"optimization":[6,25,69,197,217],"(GMPA)":[7],"algorithm":[8],"to":[9,23,85,96,126,155,169],"effectively":[10,131],"address":[11],"the":[12,16,33,39,54,59,133,150],"inherent":[13],"limitations":[14],"of":[15,80,135],"Grey":[17],"Wolf":[18],"Optimizer":[19],"(GWO)":[20],"when":[21],"applied":[22],"complex":[24,66,204],"scenarios.":[26,83],"Specifically,":[27],"GMPA":[28,112,140,189],"integrates":[29],"essential":[30],"features":[31,153],"from":[32,58,93],"Marine":[34],"Predators":[35],"Algorithm":[36],"(MPA)":[37],"into":[38],"GWO":[40,171],"framework,":[41],"enabling":[42],"superior":[43,166],"performance":[44],"through":[45],"enhanced":[46],"exploration":[47,129],"and":[48,75,98,107,123,160,172,182,195,203,211],"exploitation":[49,159],"balance.":[50],"The":[51],"evaluation":[52],"utilizes":[53],"GTOPX":[55,186],"benchmark":[56],"dataset":[57],"European":[60],"Space":[61],"Agency":[62],"(ESA),":[63],"encompassing":[64],"highly":[65],"interplanetary":[67],"trajectory":[68,206],"problems":[70],"characterized":[71],"by":[72],"pronounced":[73],"nonlinearity":[74],"multiple":[76],"conflicting":[77],"objectives":[78],"reflective":[79],"real-world":[81],"aerospace":[82,205],"Central":[84],"GMPA's":[86,165],"methodology":[87],"is":[88],"elite":[90],"matrix,":[91],"borrowed":[92],"MPA,":[94,156],"designed":[95],"preserve":[97],"refine":[99],"high-quality":[100],"solutions":[101],"iteratively,":[102],"thereby":[103],"promoting":[104],"solution":[105,183],"diversity":[106],"minimizing":[108],"premature":[109],"convergence.":[110],"Furthermore,":[111],"incorporates":[113],"a":[114,192],"three-phase":[115],"position":[116],"updating":[117],"mechanism":[118],"combined":[119],"with":[120],"L\u00e9vy":[121],"flights":[122],"Brownian":[124],"motion":[125],"significantly":[127],"bolster":[128],"capabilities,":[130],"mitigating":[132],"risk":[134],"stagnation":[136],"in":[137,214],"local":[138],"optima.":[139],"dynamically":[141],"retains":[142],"historical":[143],"information":[144],"on":[145],"promising":[146],"search":[147],"areas,":[148],"leveraging":[149],"memory":[151],"storage":[152],"intrinsic":[154],"facilitating":[157],"targeted":[158],"refinement.":[161],"Empirical":[162],"evaluations":[163],"demonstrate":[164],"effectiveness":[167],"compared":[168],"traditional":[170],"other":[173],"metaheuristic":[175,216],"algorithms,":[176],"achieving":[177],"markedly":[178],"improved":[179],"convergence":[180],"rates":[181],"quality":[184],"across":[185],"benchmarks.":[187],"Consequently,":[188],"emerges":[190],"as":[191],"robust,":[193],"efficient,":[194],"adaptive":[196],"approach":[198],"particularly":[199],"suitable":[200],"for":[201],"high-dimensional":[202],"optimization,":[207],"offering":[208],"significant":[209],"insights":[210],"practical":[212],"advancements":[213],"techniques.":[218]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}