Secondary Titles (2)
- Jack R. Wentworth Professor
- Professor of Decision Sciences
Industry Expertise (2)
Areas of Expertise (5)
Decision Support Systems
Supply Chain Management
Enterprise Resource Planning
Undergraduate Program Innovative Teaching Award (e-Enterprise Institute) (professional)
Undergraduate Program Innovative Teaching Award (SAP Curriculum) (professional)
Harry C. Sauvain Undergraduate Business Teaching Excellence Award (professional)
nspiration and Guidance Award, Doctoral Program (professional)
1991 and 1997
MBA Association Distinguished Professor (professional)
Texas A&M University: Ph.D., Business Analysis 1987
Texas A&M University: M.S., Business Computing Science 1984
University of Madras: B.E., Mechanical Engineering 1980
Genetic Search and the Dynamic Facility Layout ProblemComputers and Operations Research
1992 This research examines the suitability of genetic algorithms to the problem of facility layout over time. Genetic algorithms use the principles of genetics to evolve an initial population of solutions into a population of superior solutions. One advantage of this approach is its ability to include multiple constraints as well as non-linear and non-convex objective functions. We present a genetic procedure for the multi-period facility layout problem and report results for two test problems.
A Branch and Bound Algorithm for Flow Path Design of Automated Guided Vehicle SystemsNaval Research Logistics
1991 An algorithm for determining the optimal, unidirectional flow path for an automated guided vehicle system with a given facility layout is presented. The problem is formulated as an integer program. The objective is to minimize the total distance traveled by vehicles subject to the constraint that the resulting network consists of a single strongly connected component. A specialized branch-and-bound solution procedure is discussed in detail.
An Efficient Decision Support System for Academic Course SchedulingOperations Research
1989 This paper describes a network-based decision support system approach to the most general form of the academic course scheduling problem. The dimensions of faculty, subject, time, and room are considered by incorporating a penalty function into a network optimization approach. The approach, based on a network algorithm, is capable of solving very large problems. This methodology can be applied to other scheduling situations where there are competing objectives and multiple resources. Such situations include: scheduling of exams, times, and rooms in an academic setting, and scheduling of clients, times, and facilities for physicians, hospitals, dentists, counselors, and clinics. Common problems in such settings include the utilization of available space, and dissatisfaction with assigned times and locations. The proposed system results in more effective room utilization patterns, improved instructor satisfaction levels, and streamlines the tedious scheduling process. We describe the use of the model to schedule all graduate and undergraduate courses in the College of Business Administration at Texas A&M University. This involves 175 faculty, over 300 sections, 20 rooms, and 16 time slots for each semester's scheduling problem.