A mathematical modeling framework for scheduling and managing multiple concurrent tasks
Occurrence of human error in highly complex systems, such as a cockpit, can be disastrous and/or overwhelmingly costly. Mismanagement of multiple concurrent tasks has been observed by researchers to be a type of repetitive human error in previous studies of accidents and incidents. This error may oc...
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ndltd-ORGSU-oai-ir.library.oregonstate.edu-1957-311652012-07-20T03:13:57ZA mathematical modeling framework for scheduling and managing multiple concurrent tasksShakeri, ShakibTask analysis -- Mathematical modelsDecision making -- Mathematical modelsManagement science -- Mathematical modelsOccurrence of human error in highly complex systems, such as a cockpit, can be disastrous and/or overwhelmingly costly. Mismanagement of multiple concurrent tasks has been observed by researchers to be a type of repetitive human error in previous studies of accidents and incidents. This error may occur in the form of wrong selection of a strategy to attend to tasks, and/or wrong assessment of a task's priority at each moment. The desire to prevent such errors forms two essential questions: 1) Is there any (near) optimal method of managing multiple concurrent tasks? 2) How optimally do human operators manage these tasks? To answer the first question, operations research as it is applied to single machine scheduling was used. The operator was assumed to be a single resource that attended to different tasks, one at a time. To answer the second question, a software environment was developed to measure the human's multitasking performance, which was then compared with the answer to question one. In this research, the operator's quality of performance was maximized as opposed to the number of tasks accomplished, which was considered by previous researchers. A metaphor of 'Juggler and spinning plates' along with a graphic bar illustration was used to resemble an operator (a juggler) who manages several tasks (plates on vertical poles) concurrently. Several mixed (binary) integer-linear programming models were developed discretely over time. One model was selected and solved by the means of tabu search heuristic method. In tabu search, the significance of different initial solution finding mechanisms and different applications of long-term memory was investigated. A conjecturing method, within the tabu search, was introduced for solving problems with very large planning horizons. In all cases, tabu search gave good quality solutions in a much shorter time than branch-and-bound. Under five different scenarios, ten subjects were studied while managing multiple concurrent tasks in the software environment. None of the subjects could gain a score better than tabu search in any of the scenarios. Subjects' patterns of attendance to tasks were analyzed and compared against the pattern suggested by tabu search, and similarities/differences were identified.Graduation date: 2003Logendran, Rasaratnam2012-07-19T17:23:50Z2012-07-19T17:23:50Z2002-09-202002-09-20Thesis/Dissertationhttp://hdl.handle.net/1957/31165en_US |
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Task analysis -- Mathematical models Decision making -- Mathematical models Management science -- Mathematical models |
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Task analysis -- Mathematical models Decision making -- Mathematical models Management science -- Mathematical models Shakeri, Shakib A mathematical modeling framework for scheduling and managing multiple concurrent tasks |
description |
Occurrence of human error in highly complex systems, such as a cockpit, can be
disastrous and/or overwhelmingly costly. Mismanagement of multiple concurrent
tasks has been observed by researchers to be a type of repetitive human error in
previous studies of accidents and incidents. This error may occur in the form of
wrong selection of a strategy to attend to tasks, and/or wrong assessment of a task's
priority at each moment.
The desire to prevent such errors forms two essential questions: 1) Is there any
(near) optimal method of managing multiple concurrent tasks? 2) How optimally
do human operators manage these tasks? To answer the first question, operations
research as it is applied to single machine scheduling was used. The operator was
assumed to be a single resource that attended to different tasks, one at a time. To
answer the second question, a software environment was developed to measure the
human's multitasking performance, which was then compared with the answer to
question one.
In this research, the operator's quality of performance was maximized as opposed
to the number of tasks accomplished, which was considered by previous
researchers. A metaphor of 'Juggler and spinning plates' along with a graphic bar
illustration was used to resemble an operator (a juggler) who manages several tasks
(plates on vertical poles) concurrently.
Several mixed (binary) integer-linear programming models were developed
discretely over time. One model was selected and solved by the means of tabu
search heuristic method. In tabu search, the significance of different initial solution
finding mechanisms and different applications of long-term memory was
investigated. A conjecturing method, within the tabu search, was introduced for
solving problems with very large planning horizons. In all cases, tabu search gave
good quality solutions in a much shorter time than branch-and-bound.
Under five different scenarios, ten subjects were studied while managing multiple
concurrent tasks in the software environment. None of the subjects could gain a
score better than tabu search in any of the scenarios. Subjects' patterns of
attendance to tasks were analyzed and compared against the pattern suggested by
tabu search, and similarities/differences were identified. === Graduation date: 2003 |
author2 |
Logendran, Rasaratnam |
author_facet |
Logendran, Rasaratnam Shakeri, Shakib |
author |
Shakeri, Shakib |
author_sort |
Shakeri, Shakib |
title |
A mathematical modeling framework for scheduling and managing multiple concurrent tasks |
title_short |
A mathematical modeling framework for scheduling and managing multiple concurrent tasks |
title_full |
A mathematical modeling framework for scheduling and managing multiple concurrent tasks |
title_fullStr |
A mathematical modeling framework for scheduling and managing multiple concurrent tasks |
title_full_unstemmed |
A mathematical modeling framework for scheduling and managing multiple concurrent tasks |
title_sort |
mathematical modeling framework for scheduling and managing multiple concurrent tasks |
publishDate |
2012 |
url |
http://hdl.handle.net/1957/31165 |
work_keys_str_mv |
AT shakerishakib amathematicalmodelingframeworkforschedulingandmanagingmultipleconcurrenttasks AT shakerishakib mathematicalmodelingframeworkforschedulingandmanagingmultipleconcurrenttasks |
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1716392580824956928 |