Abstract
We study the implementation of two fundamentally different algorithms for solving the maximum flow problem: Dinic's method and the network simplex method. For the former, we present the design of a storage-efficient implementation. For the latter, we develop a "steepest-edge" pivot selection criterion that is easy to include in an existing network simplex implementation. We compare the computational efficiency of these two methods on a personal computer with a set of generated problems of up to 4 600 nodes and 27 000 arcs.
Similar content being viewed by others
References
M.J. Best and K. Ritter,Linear Programming: Active Set Analysis and Computer Programs (Prentice-Hall, Englewood Cliffs, New Jersey, 1985).
R.V. Cherkasky, Algorithms of construction of maximum flow in networks with complexityO(V 2√E) operations, Mathematical Methods of Solution of Economical Problems 7(1977)112 (in Russian).
W.H. Cunningham, A network simplex method, Math. Progr. 1(1976)105.
W.H. Cunningham, Theoretical properties of the network simplex method, Math. of Oper. Res. 4(1979)196.
T-Y. Cheung, Computational comparison of eight methods for the maximum network flow problem, ACM Trans. on Math. Software 6(1980)1.
E.A. Dinic, Algorithms for solution of a problem of maximum flow in networks with power estimation, Sov. Math. Doklady 11(1970)1277.
J. Edmonds and R.M. Karp, Theoretical improvements in algorithmic efficiency for network flow problems, J. Assoc. Computing Machinery 19(1972)248.
S. Even,Graph Algorithms (Computer Science Press, Potomac, Maryland, 1979).
L.R. Ford, Jr. and D.R. Fulkerson, Maximal flow through a network, Can. J. Math. 8(1956)399.
L.R. Ford, Jr. and D.R. Fulkerson,Flows in Networks (Princeton University Press, New Jersey, 1962).
Z. Galil, AnO(V 5/3 E 2/3) algorithm for the maximum flow problem, Acta Informatica 14(1980)221.
Z. Galil and A. Naamad, AnO(EV log2 V) algorithm for the maximum flow problem, J. Comput. Syst. Sci. 21(1980)203.
A.V. Goldberg and R.E. Tarjan, A new approach to the maximum flow problem,18th Annual ACM Symp. on Theory of Computing (1986) pp. 136–146.
F. Glover, D. Klingman, J. Mote and D. Whitman, An extended abstract of an indepth algorithmic and computational study for maximum flow problems, Discr. Appl. Math. 2(1980)251.
D. Goldfarb, Steepest edge simplex algorithms for network flow problems, Technical Report RC 6649, T.J. Watson Research Laboratory, IBM Corporation, Yorktown Heights, New York (1977).
D. Goldfarb and J.K. Reid, A practicable steepest-edge simplex algorithm, Math. Progr. 12(1977)361.
D. Goldfarb and M.D. Grigoriadis, An efficient steepest edge algorithm for the maximum flow problem, paper presented at theXth Int. Symp. on Math. Progr., Montreal, Canada (1979).
M.D. Grigoriadis, An efficient implementation of the network simplex method, Math. Progr. Study 26(1986)83.
M.D. Grigoriadis, RMFGEN — A generator for a class of maximum flow networks (in preparation).
M.D. Grigoriadis and T. Hsu, RNET, SIGMAP Bulletin (1978).
P.M.J. Harris, Pivot selection methods of the Devex LP code, Math. Progr. 5(1973)1.
E. Johnson, Networks and basic solutions, Oper. Res. 14(1966)619.
R.M. Karp, A characterization of the minimum cycle mean in a digraph, Discr. Math. 23(1978)309.
A.V. Karzanov, Determining the maximal flow in a network by the method of preflows, Sov. Math. Doklady 15(1974)434.
H.W. Kuhn and R.E. Quandt, An experimental study of the simplex method, in:Proc. of Symposia in Applied Math., Vol. XV, ed. Metropolis et al. (Amer. Math. Assoc., 1963).
E.L. Lawler,Combinatorial Optimization: Networks and Matroids (Holt, Rinehart and Winston, New York, 1976).
V.M. Malhotra, M. Pramodh Kumar and S.N. Maheshwari, AnO(|V|3) algorithm for finding maximum flows in networks, Inf. Proc. Lett. 7(1978)277.
J.M. Mulvey, Pivot strategies for primal-simplex network codes, J. Assoc. Computing Mach. 25(1978)266.
C. Papadimitriou and K. Steiglitz,Combinatorial Optimization: Algorithms and Complexity (Prentice-Hall, Englewood Cliffs, New Jersey, 1982).
Y. Shiloach, AnO(nI log2 I) maximum flow algorithm, Technical Report Stan-CS-78-802, Computer Science Department, Stanford University, California (1978).
Y. Shiloach and U. Vishkin, AnO(n 2 logn) parallel max-flow algorithm, J. Algorithms 3(1982)128.
D.D. Sleator, AnO(nm logn) algorithm for maximum network flows, Technical Report Stan-CS-80-831, Computer Science Department, Stanford University, California (1978).
D.D. Sleator and R.E. Tarjan, A data structure for dynamic trees, J. Computer and System Sci. 24(1983)362.
R.E. Tarjan,Data Structures and Network Algorithms (Society for Industrial and Applied Mathematics, Philadelphia, Pennsylvania, 1983).
R.E. Tarjan, A simple version of Karzanov's blocking flow algorithm, Oper. Res. Lett. 2(1984)265.
N. Zadeh, More pathological examples for network flow problems, Math. Progr. 5(1973)217.
P. Wolfe and L. Cutler, Experiments in linear programming, in:Recent Advances in Mathematical Programming, ed. Graves and Wolfe (McGraw-Hill, 1963).
Author information
Authors and Affiliations
Additional information
This research was supported in part by the National Science Foundation under Grant Nos. MCS-8113503 and DMS-8512277.
Rights and permissions
About this article
Cite this article
Goldfarb, D., Grigoriadis, M.D. A computational comparison of the dinic and network simplex methods for maximum flow. Ann Oper Res 13, 81–123 (1988). https://doi.org/10.1007/BF02288321
Issue Date:
DOI: https://doi.org/10.1007/BF02288321