"This thesis explains a productive collaboration framework where companies compete and collaborate simultaneously in an auction based virtual marketplace. The thesis describes the control center of each company in this environment and proposes algorithms for the Scheduler and Estimator agents in this framework. A job shop scheduling heuristic algorithm for varying reward structures is proposed, which is an indexing algorithm that schedules tasks for each time unit, using dynamic allocation indices and binary integer programming. It is shown that the heuristic performs well against known reward based scheduling methods. An estimation decision system based on this scheduling algorithm is also presented that not only utilizes the Scheduler agent in task selection, but also uses concepts such as company reputation and aggressiveness. The integration of these agents result in a decision system for estimating and scheduling tasks with varying reward structures in a job-shop-like environment, which combines sound management science principles in order to emphasize analytical solutions to complicated real-life problems"--Abstract, page iii.
Grasman, Scott E. (Scott Erwin)
Leu, M. C. (Ming-Chuan)
Engineering Management and Systems Engineering
M.S. in Engineering Management
University of Missouri--Rolla
viii, 68 pages
© 2005 Evren Akcora, All rights reserved.
Thesis - Restricted Access
Production scheduling -- Mathematical models
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Electronic access to the full-text of this document is restricted to Missouri S&T users. Otherwise, request this publication directly from Missouri S&T Library or contact your local library.http://merlin.lib.umsystem.edu/record=b5422544~S5
Akcora, Evren, "A decision system for estimating and scheduling tasks with varying reward structures in a job shop environment" (2005). Masters Theses. 4434.
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