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Massachusetts Institute of Technology

Managerial factors affecting aircraft maintenance : an agent based model and optimization with simulated annealing

Abstract

dc:description.abstract

A single objective agent based model of managerial factors affecting aircraft maintenance was build based on a case study done regarding safety climate's effect on maintenance efficacy in the Korean Air Force. In particular the model measures the effect of managerial context and command on agents' motivation and efficacy. The model is then optimized using a simulated annealing algorithm. Input parameters were varied to ensure reliability and repeatability of results. The model's sensitivity, in terms of optimal input vector and results, were also tested across a variety of input parameters. Results suggested that across all input parameters two managerial contexts dominated: contingent reward systems and laissez-faire.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Engineering Systems Division.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2015

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Hamilton, Douglas (Douglas Maxwell)
Advisor dc:contributor.advisor
  • Daniel D Frey.

Subjects

dc:subject × 2

Rights

dc:rights
Statement dc: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.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/100377
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/100377

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Hamilton, Douglas (Douglas Maxwell). Managerial factors affecting aircraft maintenance : an agent based model and optimization with simulated annealing. Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/100377