Minimum-Cost Strong Network Orientation Problems: Classification, Complexity, and Algorithms

In the minimum-cost strong network orientation problem (MCSO), we are given an undirected graph G = (V, E) with nonnegative edge lengths l(e) and a transportation schedule T = {(s(1), t(1), W(1)), . . ., (S(k), t(k), W(k))}, where w(i) units of weight have to be transported from the source vertex s(i) to the target vertex t(i) for i = 1,..., k. Let G(power sigma) be a strongly connected orientation of G and let L(andis,power sigma) be the length of the shortest (directed) path from s(i) to t(i) in G(power sigma). The goal in the MCSO is to find a strongly connected orientation G(power sigma) such that the overall cost of the orientation given by sum w(i) l(i) (sum case) or max w(i) l(i) (bottleneck case) is minimized. The strong network orientation problem is motivated by the practical problem of designing the optimal unidirectional flow path of automated guided vehicles. In this paper, we investigate the MCSO from the algorithmic and complexity points of view and propose a classification scheme. In the first part of the paper, we identify several efficiently solvable cases of the MCSO with sum and bottleneck objective functions which arise if additional restrictions are imposed on the structure of the graph G, the edge lengths l(e), and/or the transportation schedule T. In the second part, we identify special cases of the MCSO which are NP-hard. © 1999 John Wiley & Sons, inc. Networks 33: 5770,1999