2026-09-19T04:58:55Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/532992022-01-13T07:54:48Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Stephan E. Kolitz and Hamsa Balakrishnan.
Negron, Blair Ellen Leake
Massachusetts Institute of Technology. Operations Research Center.
Massachusetts Institute of Technology. Operations Research Center
Sloan School of Management
2010-03-25T15:28:09Z
2010-03-25T15:28:09Z
2009
2009
http://hdl.handle.net/1721.1/53299
549278958
Thesis (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2009.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 133-135).
Unmanned aerial vehicles are being incorporated in an increasing variety of operations. To take full advantage of the vehicles, the plans for the operations should integrate each vehicle's capabilities when planning the operations. This thesis focuses on planning operations for multiple, heterogeneous UAVs for the purpose of monitoring Earth's phenomena through data collection. The planning is done for flight in three dimensions. The problem also includes time window constraints for data collection and incorporates human input in the planning process. Two solution methods are presented: (1) a mixed-integer program, and (2) an algorithm that utilizes a meta-heuristic to generate composite variables for a linear program, called the Composite Operations Planning Algorithm. The suitability of the two methods to solve the operations planning problem is compared based on the ability of each of the methods to find high-value, feasible solutions for large-scale, operationally sized problems in a reasonable amount of time. The analysis shows that the Composite Operations Planning Algorithm can develop operations plans for problems including 15 UAVs and 5000 nodes in less than 25 minutes using a desktop computer.
by Blair Ellen Leake Negron.
S.M.
135 p.
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by
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http://dspace.mit.edu/handle/1721.1/7582
Operations Research Center.
Operational planning for multiple heterogeneous unmanned aerial vehicles in three dimensions
Thesis
application/pdf
Publication
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<Abstract>Unmanned aerial vehicles are being incorporated in an increasing variety of operations. To take full advantage of the vehicles, the plans for the operations should integrate each vehicle's capabilities when planning the operations. This thesis focuses on planning operations for multiple, heterogeneous UAVs for the purpose of monitoring Earth's phenomena through data collection. The planning is done for flight in three dimensions. The problem also includes time window constraints for data collection and incorporates human input in the planning process. Two solution methods are presented: (1) a mixed-integer program, and (2) an algorithm that utilizes a meta-heuristic to generate composite variables for a linear program, called the Composite Operations Planning Algorithm. The suitability of the two methods to solve the operations planning problem is compared based on the ability of each of the methods to find high-value, feasible solutions for large-scale, operationally sized problems in a reasonable amount of time. The analysis shows that the Composite Operations Planning Algorithm can develop operations plans for problems including 15 UAVs and 5000 nodes in less than 25 minutes using a desktop computer.</Abstract>
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