Network Flow Problems in Constraint Programming
CP '01 Proceedings of the 7th International Conference on Principles and Practice of Constraint Programming
Optimality study of resource binding with multi-Vdds
Proceedings of the 43rd annual Design Automation Conference
Behavioral synthesis with activating unused flip-flops for reducing glitch power in FPGA
Proceedings of the 2008 Asia and South Pacific Design Automation Conference
Computers & Mathematics with Applications
Operations Research Letters
A Network Simplex Algorithm for the Equal Flow Problem on a Generalized Network
INFORMS Journal on Computing
Hi-index | 0.01 |
The minimum cost flow problem is to determine a least cost shipment of a commodity through a network G = (N, A) in order to satisfy demands at certain nodes from available supplies at other nodes. In this paper, we study a variant of the minimum cost flow problem where we are given a set [math not displayed] of arcs and require that each arc in R must carry the same amount of flow. This problem, which we call the simple equal flow problem, arose while modeling a water resource system management in Sardinia, Italy. We consider the simple equal flow problem in a directed network with n nodes, m arcs, and where all arc capacities and node supplies are integer and bounded by U. We develop several algorithms for the simple equal flow problem-the network simplex algorithm, the parametric simplex algorithm, the combinatorial parametric algorithm, the binary search algorithm, and the capacity scaling algorithm. The binary search algorithm solves the simple equal flow problem in O(log(nU)) applications of any minimum cost flow algorithm. The capacity scaling algorithm solves it in O(m(m + n log n) log (nU)) time, which is almost the same time needed to solve the minimum cost flow problem by the capacity scaling algorithm. These algorithms can be easily modified to obtain an integer solution of the simple equal flow problem.