Suming Wu
Knowledge Systems, Inc.
Stafford, Texas
L. Ridgway Scott
Department of Computer Science
University of Chicago
E. Andrew Boyd
PROS Revenue Management
Houston, Texas
Abstract: We address the problem of minimizing the fuel consumption incurred by compressor stations in steady-state natural gas transmission networks. In the real world, these type of instances are very large both in terms of the number of decision variables and the number of constraints, and very complex due to the presence of non-linearity and non-convexity in both the set of feasible solutions and the objective function. In this paper we present a study of the properties of gas pipeline networks, and exploit them to develop a technique that can be used to significantly reduce the size of the instances, without disrupting problem structure, making it more amenable to optimization methodologies.