Finding Maximum Minimum Cost Flows to Evaluate Gas Network Capacities

Abstract

In this article we consider the following problem arising in the context of scenario generation to evaluate the transport capacity of gas networks: In the Uncapacitated Maximum Minimum Cost Flow Problem (UMMCF) we are given a flow network where each arc has an associated nonnegative length and infinite capacity. Additionally, for each source and each sink a lower and an upper bound on its supply and demand are known, respectively. The goal is to find values for the supplies and demands respecting these bounds, such that the optimal value of the induced Minimum Cost Flow Problem is maximized, i.e., to determine a scenario with maximum transportmoment. In this article we propose two linear bilevel optimization models for UMMCF, introduce a greedy-style heuristic, and report on our first computational experiment.