Aral Bahadir, ISEN Ph.D. Candidate
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Advisor: Dr. Georgia-Ann Klutke
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"Scheduling Screening and Inspections"
Short Bio:
Bahadir Aral is a Ph.D. candidate in the Department of Industrial and Systems Engineering at Texas A&M University. He obtained the BS from Bogazici University and the MS from Texas A&M University, both in Industrial Engineering. His research interests are the scheduling inspections for the stochastic maintained systems.

Seminar Abstract:
For a maintained system with non-self-announcing failures, it is important to develop an effective inspections strategy to improve the system performance measure. Due to the fact that the amount of resources are not unlimited, the number of inspections performed will not unlimited either. In this talk, I will talk about how to improve the system availability for a fixed inspection rate when failure occurs according to a non-homogenous Poisson point process.

Greg Graves, ISEN Ph.D. Candidate
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Advisor: Dr. Martin A. Wortman
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"A Risk Theoretic Approach to Forward Operating Base Security"
Short Bio:
Greg Graves graduated from West Point in 1988 with a B.S. in Engineering Management. He has served in the Army since then in various capacities including the artillery and transportation/logistics in such locations as Colorado, Virginia, Egypt, and Haiti in the process. In 1998, after completing a M.S. at Texas A&M in industrial engineering, he reported to the Department of Mathematical Sciences at West Point where he performed research and taught for three years. He was subsequently assigned as an operations research analyst at Fort Lee, Virginia and worked on future logistical concepts for the Army. In 2003, he returned to Texas A&M to pursue a Ph.D.. He was promoted to Lieutenant Colonel in 2005 and will return to West Point to teach math again this summer.

Seminar Abstract:
The decision of how to best allocate resources for force protection must be made under a significant amount of uncertainty and ambiguity. This research provides a formulation of a mathematical model to evaluate alternative allocations of resources when a unique probability measure on the sample space is not specified for each alternative. An objective function is identified which can order preferences for the decision maker, and conditions for separation of preferences when complete characterization of probability law is not provided are examined.

Ahmet Reha Botsali, ISEN Ph.D. Candidate
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Advisor: Dr. Georgia-Ann Klutke
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Advisor: Dr. Brett A. Peters
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"Layout Design Models for Retail Stores"
Short Bio:
Ahmet Reha Botsalı, is a Ph.D. candidate in the Department of Industrial and Systems Engineering at Texas A&M University. He got his BS and MS degrees in industrial engineering at Bilkent University, Turkey. In 2000, he started his PhD study at Texas A&M University in Industrial Engineering. His research interests are layout design and scheduling.

Seminar Abstract:
Layout design problem has a long and rich past in operations research literature. Traditionally, this problem is analyzed in the context of manufacturing and distribution facilities and many effective solution techniques have been developed. Our research focuses on retail store layout design problem. To the best of our knowledge, there is not a quantitative model for this problem in the literature. In this study, we compare the analogies and the differences between the retail store layout design problem and the existing layout design problems studied before. We provide layout design models that are specific to retail stores, and also analyze their performance with respect to impulse purchase revenue and customer travel distance.

Fatih Mutlu, ISEN Ph.D. Candidate
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Advisor: Dr. Sila Cetinkaya
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"An Analytical Model for a Time-and-Quantity Based Consolidation Policy"
Short Bio:
Fatih Mutlu received his B.S. in Industrial Engineering from Bilkent University, Turkey in 2000. In September 2000, he enrolled in the doctoral program at Texas A\&M University, Department of Industrial Engineering. His research interests are in supply chain management, inventory theory, stochastic modeling, and optimization.

Seminar Abstract:
Shipment Consolidation is a logistics strategy that combines small size loads at the aim of benefiting from transportation scale economies. Time-and-quantity policy is a shipment consolidation policy which aims to consolidate a target load, but by time T shipment is released if the required load is not accumulated. I will talk about an analytical model for computing the expected annual cost for time-and-quantity policy. I will also compare the cost and service performances of time-and-quantity policy to time policy and quantity policy.

Anshu Jalora, ISEN Ph.D. Candidate
Contact: Email - Webpage
Advisor: Dr. Brett A. Peters
Contact: Email - Webpage

"Order Acceptance and Scheduling at an On-Date Delivery Make-to-Order Manufacturing System using Revenue Management"
Short Bio:
Anshu Jalora is a Ph.D. Candidate in the Department of Industrial and Systems Engineering at Texas A&M University. He received his undergraduate degree in Mechanical Engineering from Indian Institute of Technology, New Delhi, India in 1998. His research interests are in the areas of stochastic dynamic programming, stochastic programming, mixed integer programming, meta- heuristic optimization, simulation and stochastic approximation with applications in revenue management, logistics, facilities planning and design, supply chain management and material handling systems.

Seminar Abstract:
Recent trends in manufacturing industry indicate an increasing inclination towards make-to-order systems. In addition, consumers, like Dell Computers who have pioneerered 'lean practices' in their operations, are demanding on- date deliveries of raw materials from their suppliers. In this seminar, I will address these trends and present a revenue management model for accepting and scheduling customer orders at an on-date delivery make-to- order manufacturing system.