Agent-Based Modelling of Stress and Productivity Performance in the Workplace

dc.contributor.advisorAshlock, Daniel
dc.contributor.authorPage, Matthew
dc.date.accessioned2013-08-23T14:55:48Z
dc.date.available2013-08-23T14:55:48Z
dc.date.copyright2013-07
dc.date.created2013-07-25
dc.date.issued2013-08-23
dc.degree.departmentDepartment of Mathematics and Statisticsen_US
dc.degree.grantorUniversity of Guelphen_US
dc.degree.nameMaster of Scienceen_US
dc.degree.programmeMathematics and Statisticsen_US
dc.description.abstractThe ill-effects of stress due to fatigue significantly impact the welfare of individuals and consequently impact overall corporate productivity. This study introduces a simplified model of stress in the workplace using agent-based simulation. This study represents a novel contribution to the field of evolutionary computation. Agents are encoded initially using a String Representation and later expanded to multi-state Binary Decision Automata to choose between work on a base task, special project or rest. Training occurs by agents inaccurately mimicking behaviour of highly productive mentors. Stress is accumulated through working long hours thereby decreasing productivity performance of an agent. Lowest productivity agents are fired or retrained. The String representation for agents demonstrated near average performance attributed to the normally distributed tasks assigned to the string. The BDA representation was found to be highly adaptive, responding robustly to parameter changes. By reducing the number of simplifications for the model, a more accurate representation of the real world can be achieved.en_US
dc.identifier.urihttp://hdl.handle.net/10214/7411
dc.language.isoenen_US
dc.publisherUniversity of Guelphen_US
dc.rightsAttribution-NoDerivs 2.5 Canada*
dc.rights.urihttp://creativecommons.org/licenses/by-nd/2.5/ca/*
dc.subjectStressen_US
dc.subjectComputational Intelligenceen_US
dc.subjectAgent-Based Modellingen_US
dc.subjectEvolutionary Computationen_US
dc.titleAgent-Based Modelling of Stress and Productivity Performance in the Workplaceen_US
dc.typeThesisen_US

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