Thesis: S.M., Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2015. / This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. / Cataloged from student-submitted PDF version of thesis. / Includes bibliographical references (pages 95-97). / In this thesis, we introduce and analyze models for air asset scheduling within a military theater. Specifically, we seek to create models that generate aircraft-specific schedules for Air Tasking Orders (ATOs) within a Joint Aerospace Operations Center (JAOC). A JAOC provides command and control of all air and space assets tasked to a particular region/area of responsibility (AOR) or strategic command. Scheduling these assets requires a high level of unified effort whereby centralized planning must be handled in a decentralized fashion and is known as the Air Tasking Cycle. Given the complexity of this process, subject matter experts from diverse backgrounds are required to design and plan missions for most operations. In addition, the difficulty of the process dictates that mission prioritization and aircraft/munitions allocation are separated in the cycle, sacrificing some global perspective for the sake of efficiency in the scheduling process. We present a modeling framework that allows planners to simultaneously select missions and assign aircraft/munitions to the missions, allowing for the optimal air asset scheduling toward the pursuit of theater-level objectives. This flexible framework takes into account air refueling considerations as well as the need for certain missions to be completed by "packages" of particular aircraft types. We submit heuristic, mixed integer optimization (MIO), and hybrid models within this structure and analyze the value of their schedules and the corresponding trade-offs with computational solve time.0 / by Kevin Joseph Rossillon. / S.M.
Identifer | oai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/98562 |
Date | January 2015 |
Creators | Rossillon, Kevin Joseph |
Contributors | Sung-Hyun Son and Dimitris Bertsimas., Massachusetts Institute of Technology. Operations Research Center., Massachusetts Institute of Technology. Operations Research Center. |
Publisher | Massachusetts Institute of Technology |
Source Sets | M.I.T. Theses and Dissertation |
Language | English |
Detected Language | English |
Type | Thesis |
Format | 97 pages, application/pdf |
Rights | M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission., http://dspace.mit.edu/handle/1721.1/7582 |
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