Masters Theses


Evren Akcora


"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)
Saygin, Can

Committee Member(s)

Leu, M. C. (Ming-Chuan)


Engineering Management and Systems Engineering

Degree Name

M.S. in Engineering Management


The research was funded by the National Science Foundation through the grant DMI-0323028.


University of Missouri--Rolla

Publication Date

Spring 2005


viii, 68 pages

Note about bibliography

Includes bibliographical references (pages 66-67).


© 2005 Evren Akcora, All rights reserved.

Document Type

Thesis - Restricted Access

File Type




Subject Headings

Job shops
Production scheduling -- Mathematical models

Thesis Number

T 8743

Print OCLC #


Link to Catalog Record

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