Trajectory optimization is and will remain a hot topic in the engineering field. Because analytical or exact solutions are often difficult and sometimes impossible to compute, there is a need for alternative and efficient methods. UnderWater Vehicles (UWV) trajectories and rendezvous trajectories of continuous low-thrust spacecraft are examined. One of the methods to solve such problems is the Genetic Algorithm (GA) method. In this work, a GA has been developed using Matlab®. It treats possible solutions to the studied problems as individuals and eventually converges to an optimal or near optimal solution. Genetic Algorithms have been used previously to solve chaser-target type of rendezvous trajectories. Here, active rendezvous trajectories have been successfully solved using Genetic Algorithms.
","abstract_html":"<p>Trajectory optimization is and will remain a hot topic in the engineering field. Because analytical or exact solutions are often difficult and sometimes impossible to compute, there is a need for alternative and efficient methods. UnderWater Vehicles (UWV) trajectories and rendezvous trajectories of continuous low-thrust spacecraft are examined. One of the methods to solve such problems is the Genetic Algorithm (GA) method. In this work, a GA has been developed using Matlab®. It treats possible solutions to the studied problems as individuals and eventually converges to an optimal or near optimal solution. Genetic Algorithms have been used previously to solve chaser-target type of rendezvous trajectories. Here, active rendezvous trajectories have been successfully solved using Genetic Algorithms.</p>","abstract_has_math":false,"creators":["Ricour, Marie Emmanuelle"],"institution":null,"degree_name":"Master of Science in Aerospace Engineering","degree_level":"Thesis - Open Access","degree_discipline":"Aerospace Engineering","degree_department":null,"school":null,"contributors":["Yechiel J. Crispin","Ossama Abdelkhalik","Eric Perrell"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2006,"date_issued":"2006-10-01T07:00:00Z","date_published":"2006-10-01T07:00:00Z","updated_at":"2026-07-27T19:25:37Z","subjects":["optimization","rendezvous","trajectories","genetic algorithms","Aerospace Engineering","Astrodynamics","Navigation, Guidance, Control and Dynamics"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://commons.erau.edu/db-theses/235","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Yechiel J. Crispin","Ossama Abdelkhalik","Eric Perrell"]},{"key":"dc:creator","label":"Author","values":["Ricour, Marie Emmanuelle"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Aerospace Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis - Open Access"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science in Aerospace Engineering"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["optimization","rendezvous","trajectories","genetic algorithms","Aerospace Engineering","Astrodynamics","Navigation, Guidance, Control and Dynamics"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://commons.erau.edu/db-theses/235"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Trajectory optimization is and will remain a hot topic in the engineering field. Because analytical or exact solutions are often difficult and sometimes impossible to compute, there is a need for alternative and efficient methods. UnderWater Vehicles (UWV) trajectories and rendezvous trajectories of continuous low-thrust spacecraft are examined. One of the methods to solve such problems is the Genetic Algorithm (GA) method. In this work, a GA has been developed using Matlab®. It treats possible solutions to the studied problems as individuals and eventually converges to an optimal or near optimal solution. Genetic Algorithms have been used previously to solve chaser-target type of rendezvous trajectories. Here, active rendezvous trajectories have been successfully solved using Genetic Algorithms.
"]},{"key":"dc:title","label":"Title","values":["Optimization of Active Rendezvous Trajectories by Genetic Algorithms"]}]}],"canonical_facts":{"dc:contributor":["Yechiel J. Crispin","Ossama Abdelkhalik","Eric Perrell"],"dc:creator":["Ricour, Marie Emmanuelle"],"dc:description.abstract":["Trajectory optimization is and will remain a hot topic in the engineering field. Because analytical or exact solutions are often difficult and sometimes impossible to compute, there is a need for alternative and efficient methods. UnderWater Vehicles (UWV) trajectories and rendezvous trajectories of continuous low-thrust spacecraft are examined. One of the methods to solve such problems is the Genetic Algorithm (GA) method. In this work, a GA has been developed using Matlab®. It treats possible solutions to the studied problems as individuals and eventually converges to an optimal or near optimal solution. Genetic Algorithms have been used previously to solve chaser-target type of rendezvous trajectories. Here, active rendezvous trajectories have been successfully solved using Genetic Algorithms.
"],"dc:identifier":["https://commons.erau.edu/db-theses/235"],"dc:subject":["optimization","rendezvous","trajectories","genetic algorithms","Aerospace Engineering","Astrodynamics","Navigation, Guidance, Control and Dynamics"],"dc:title":["Optimization of Active Rendezvous Trajectories by Genetic Algorithms"],"thesis:degree_discipline":["Aerospace Engineering"],"thesis:degree_level":["Thesis - Open Access"],"thesis:degree_name":["Master of Science in Aerospace Engineering"]},"updated_at":"2026-07-27T19:25:37Z"}