Proceedings ArticleDOI
Draining Algorithm for the Maximum Flow Problem
Jiyang Dong,Wei Li,Congbo Cai,Zhong Chen +3 more
- Vol. 3, pp 197-200
TLDR
Experimental results shown the high efficiency of the proposed algorithm in near saturated network, thought it has the same computational complex with the traditional augmenting path approach for regular flow networks.Abstract:
A new augmenting path based algorithm called draining algorithm is proposed for the maximum flow problem in this letter. Unlike other augmenting path based algorithms which augment gradually the flow from zero-flow to the maximum flow, the proposed algorithm drains the redundant capacities out of the network to achieve the maximum flow. Experimental results shown the high efficiency of the proposed algorithm in near saturated network, thought it has a same computational complex with the traditional augmenting path approach for regular flow networks.read more
Citations
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Proceedings ArticleDOI
Diversity and Serendipity in Recommender Systems
Keneilwe Zuva,Tranos Zuva +1 more
TL;DR: This paper presents and explores a recommendation technique that ensures that diversity, accuracy and serendipity are all factored in the recommendations, and performs comparatively well as compared to other algorithms in literature.
Journal ArticleDOI
Introducing mass balancing theorem for network flow maximization
TL;DR: It is shown that this theorem suggests that the maximization of network flow can be achieved by visiting only unbalanced nodes rather than the whole network, and has also potential to make optimization an easier task in a multi-commodity flow environment.
Proceedings ArticleDOI
Fast Augmentation Algorithms for Maximising the Flow in Repairable Flow Networks After a Component Failure
TL;DR: Efficient algorithms with linear average running time O(m) in the size m of the network, are proposed for restoring the maximum flow in single-commodity and multi- commodity networks after a component failure.
Journal ArticleDOI
Two-stage distributed parallel algorithm with message passing interface for maximum flow problem
Jincheng Jiang,Lixin Wu +1 more
TL;DR: This paper presents a two-stage distributed parallel algorithm (TSDPA) with message passing interface to improve the computational performance and demonstrates that TSDPA runs 1.2–15.5 times faster than sequential algorithms and is faster than or almost as fast as the H_PRF and Q-PRF codes.
Proceedings ArticleDOI
Introducing simplex mass balancing method for multi -commodity flow network with a s eparator
TL;DR: An algorithm is developed for maximization of flow in a multi-commodity network with a separator that is present in Oil and Gas development fields and has direct practical relevance and industrial application.
References
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Book ChapterDOI
Maximal Flow Through a Network
L. R. Ford,D. R. Fulkerson +1 more
TL;DR: In this paper, the problem of finding a maximal flow from one given city to another is formulated as follows: "Consider a rail network connecting two cities by way of a number of intermediate cities, where each link has a number assigned to it representing its capacity".
Journal ArticleDOI
Theoretical Improvements in Algorithmic Efficiency for Network Flow Problems
Jack Edmonds,Richard M. Karp +1 more
TL;DR: New algorithms for the maximum flow problem, the Hitchcock transportation problem, and the general minimum-cost flow problem are presented, and Dinic shows that, in a network with n nodes and p arcs, a maximum flow can be computed in 0 (n2p) primitive operations by an algorithm which augments along shortest augmenting paths.
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Data Structures and Network Algorithms
TL;DR: This paper presents a meta-trees tree model that automates the very labor-intensive and therefore time-heavy and therefore expensive process of manually selecting trees to grow in a graph.
Theoretical Improvements in Algorithmic Efficiency for Network Flow Problems.
Jack Edmonds,Richard M. Karp +1 more
TL;DR: In this article, the authors presented new algorithms for the maximum flow problem, the Hitchcock transportation problem and the general minimum-cost flow problem and derived upper bounds on the number of steps in these algorithms.
Journal ArticleDOI
A new approach to the maximum-flow problem
TL;DR: An alternative method based on the preflow concept of Karzanov, which runs as fast as any other known method on dense graphs, achieving an O(n) time bound on an n-vertex graph and faster on graphs of moderate density.
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