University of Chicago Downtown Center
450 City Center
Room 602 (Sixth Floor)
The University of Chicago is located on the north bank of the Chicago River, one block east of Michigan Avenue, one block west of Columbus Drive (across from the NBC Tower). Parking is near Columbus and Grand Avenue.
Dr. Saigal has a B.A. (Honors) in Mathematics from St. Stephen's College, Delhi, and a Ph.D. in Mathematical Sciences from Rice University, Houston. He has consulted in a variety of industries, including electric and gas utilities, petroleum distributors, governmental agencies, and transportation companies. His project work has involved extensive use of mathematical programming and information systems techniques and products, including linear and integer programming and network algorithms, relational databases, and object-oriented program design.
Abstract. To the OR analyst, general-purpose languages such as C or FORTRAN have long been the tools of choice when prototyping and implementing mathematical programming based applications. This "black-box" approach has resulted in an image of the OR application process as alchemy: The analyst puts up slides with arcane formulae, goes off into her lair, and emerges six months later with a "trust-me" decision-support system, or worse yet, a report.
The situation has improved somewhat in recent years with the emergence of special-purpose modeling systems such as AMPL and GAMS. These specialized languages for math programming have numerous advantages over general-purpose languages. Freed from focusing on chasing pointers, the analyst can co-opt the end-user into a true model prototyping phase. The technically adept end-user may even be able to understand, kibitz, and modify the model logic. Unfortunately, the application development process remains in the OR professional's domain. The end-user is still not in the driver's seat.
The rise of embedded optimizers in commonly available spreadsheets has finally brought about the possibility that technically oriented real world users may finally begin to take control and come to regard optimization in the same light as, say, simulation or database design. Can spreadsheet solvers lead us to the long sought after iceberg of millions of potential users of optimization? Are OR professionals going to be out of a job if this catches on? Do Real Operations Researchers use spreadsheets? Does the built-in Excel Solver really optimize? The talk will examine these and other issues related to spreadsheet optimization.