L. Ridgway Scott
Department of Computer Science
University of Chicago
E. Andrew Boyd
PROS Strategic Solutions, Inc.
Houston, Texas
Roger Z. Ríos-Mercado
Department of Industrial Engineering
Texas A&M University
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 develop a technique that can be used to significantly reduce the size of the instances by exploiting the special and unique structure and properties of gas pipeline networks.