The paper presents a comparison between three approaches to solving the length-bounded maximum multicommodity flow problem with unit edge-lengths. Following the first approach, Garg and Konemann’s, we developed an improved fully polynomial time approximation scheme for this problem. As the second alternative, we considered the well-known greedy approach. | Yugoslav Journal of Operations Research XX (2018), Number , zzz–zzz DOI: ON THREE APPROACHES TO LENGTH-BOUNDED MAXIMUM MULTICOMMODITY FLOW WITH UNIT EDGE-LENGTHS Pavel BORISOVSKY Sobolev Institute of Mathematics SB RAS, 13 Pevtsov str., 644099, Omsk, Russia borisovski@ Anton EREMEEV Sobolev Institute of Mathematics SB RAS, 13 Pevtsov str., 644099, Omsk, Russia, and Dostoevsky Omsk State University, 55a pr. Mira, 644077, Omsk, Russia eremeev@ Sergei HRUSHEV Sobolev Institute of Mathematics SB RAS, 13 Pevtsov str., 644099, Omsk, Russia hrushev@ Vadim TEPLYAKOV Yaliny Research and Development Center, 2 Paveletskaya naberezhnaya, block 2, 115114, Moscow, Russia Mikhail VOROZHTSOV Yaliny Research and Development Center, 2 Paveletskaya naberezhnaya, block 2, 115114, Moscow, Russia Received: August 2018 / Accepted: December 2018 Abstract: The paper presents a comparison between three approaches to solving the length-bounded maximum multicommodity flow problem with unit edge-lengths. Following the first approach, Garg and Konemann’s, we developed an improved fully polynomial¨ time approximation scheme for this problem. As the second alternative, we considered the well-known greedy approach. The third approach is the one that yields exact solutions by means of a standard LP solver applied to an LP model on the time-expanded network. 2 P., Borisovsky et al. / Length-Bounded Maximum Multicommodity Flow Computational experiments are carried out on benchmark graphs and the graphs that model software defined satellite networks, to compare the proposed algorithms with an exact linear programming solver. The results of the experiments demonstrate a trade-off between the computing time and the precision of algorithms under consideration. Keywords: Computational Experiment, Linear Programming, Fully Polynomial-Time Approximation Scheme, Greedy .
