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Knowledge based improvement : simulation and artificial intelligence for understanding and improving decision making in an operations system
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Alifantis, Thanos (2006) Knowledge based improvement : simulation and artificial intelligence for understanding and improving decision making in an operations system. PhD thesis, University of Warwick.
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WRAP_THESIS_Alifantis_2006.pdf - Submitted Version Download (11Mb) | Preview |
Official URL: http://webcat.warwick.ac.uk/record=b2217198~S1
Abstract
The thesis investigates the possibility of using simulation for understanding and
improving the design of decision making in a real context. The approach is based on the
problem of representing decision making behaviour in Discrete Event Simulation.
An investigation of existing techniques led to the design of a methodology known as
Knowledge Based Improvement (KBI). The KBI covers the key stages of the process of
using simulation for understanding and improving the design of decision making. Using a
research strategy that involves a case study in Ford, the research tests each stage of KBI.
The thesis explains how simulation can be used for understanding real decision making
problems and for collecting the data required for modelling individual decision making
strategies. The thesis demonstrates the possibility of a simulation based knowledge
elicitation in a real context and it investigates the practical difficulties involved in this
process.
The research tests the process of understanding decision making policies by modelling
specific decision makers using Artificial Intelligence. It tests the use of simulation for
assessing the decision making strategies and it shows that simulation can be used for
identifying efficient strategies and for improving the design of decision making practices.
The thesis reports the degree of success of the approach in relation to the data that were
collected and it describes the validation checks that were undertaken. In addition, it
reports the lessons learned from the application of the KBI methodology, the overall
success of the approach and the main limitations that were identified during the
implementation.
Item Type: | Thesis (PhD) | ||||
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Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software T Technology > TS Manufactures |
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Library of Congress Subject Headings (LCSH): | Decision making -- Simulation methods, Discrete-time systems, Artificial intelligence | ||||
Official Date: | August 2006 | ||||
Dates: |
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Institution: | University of Warwick | ||||
Theses Department: | Warwick Business School | ||||
Thesis Type: | PhD | ||||
Publication Status: | Unpublished | ||||
Supervisor(s)/Advisor: | Hurrion, R. D. (Robert D.) ; Robinson, Stewart, 1964- | ||||
Sponsors: | Engineering and Physical Sciences Research Council (EPSRC) (GRJM72876) ; Ford Motor Company ; Lanner Group | ||||
Extent: | ix, 193 leaves | ||||
Language: | eng |
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