141,834 research outputs found
Improved Local Search Algorithms with Multi-Cycle Reduction for Minimum Concave Cost Network Flow Problems
The minimum concave cost network flow problem (MCCNFP) has many applications in areas such as telecommunication network design, facility location, production and inventory planning, and traffic scheduling and control. However, it is a well known NP-hard problem, and all existing search based exact algorithms are not practical for networks with even moderate numbers of vertices. Therefore, the research community also focuses on approximation algorithms to tackle the problems in practice. In this paper, we present an improved local search algorithm for the minimum concave cost network flow problem based on multi-cycle reduction. The original cycle reduction local search algorithm as proposed by Gallo and Sodini considers only negative cost single cycles; however, we find that such cycle reduction is not complete. We show that negative cost multi-cycles may exist in a network with concave edge costs that has no negative cost cycles, and an existing flow can be reduced to an adjacent neighboring flow with lower cost by redirecting flows along these negative multi-cycles. In this paper, we present an improved local search algorithm based on multi-cycle reduction. We evaluate our proposed algorithm in networks with a simple concave edge cost in different topologies and sizes. The experimental results show that the original cycle reduction algorithms can improve the quality of solutions obtained from a simple minimum cost augmentation approximation heuristic (LDF), and that a multi-cycle reduction yields more improvements; however, it reaches a point of diminished returns when we attempt to reduce more than bicycles
Cluster Before You Hallucinate: Approximating Node-Capacitated Network Design and Energy Efficient Routing
We consider circuit routing with an objective of minimizing energy, in a
network of routers that are speed scalable and that may be shutdown when idle.
We consider both multicast routing and unicast routing. It is known that this
energy minimization problem can be reduced to a capacitated flow network design
problem, where vertices have a common capacity but arbitrary costs, and the
goal is to choose a minimum cost collection of vertices whose induced subgraph
will support the specified flow requirements. For the multicast (single-sink)
capacitated design problem we give a polynomial-time algorithm that is
O(log^3n)-approximate with O(log^4 n) congestion. This translates back to a
O(log ^(4{\alpha}+3) n)-approximation for the multicast energy-minimization
routing problem, where {\alpha} is the polynomial exponent in the dynamic power
used by a router. For the unicast (multicommodity) capacitated design problem
we give a polynomial-time algorithm that is O(log^5 n)-approximate with
O(log^12 n) congestion, which translates back to a O(log^(12{\alpha}+5)
n)-approximation for the unicast energy-minimization routing problem.Comment: 22 pages (full version of STOC 2014 paper
Directed Network Design with Orientation Constraints
We study directed network design problems with orientation constraints. An orientation constraint on a pair of nodes u and v states that a feasible solution may include at most one of the arcs (u,v) and (v,u). Such constraints arise naturally in many network design problems, since link or edge resources such as fibre can be used to support traffic in one of two possible directions only. Our first result is that the directed network design problem with orientation constraints can be solved in polynomial time in the case where the requirement function f is intersecting supermodular. (The case where there no orientation constraints follows from work of Frank [6].) The second main result of the paper is a 4-approximation algorithm for the minimum cost strongly connected subgraph problem with orientation constraints. Our algorithm shows that the problem of enforcing orientation constraints can be reduced to the minimum cost 2-edge connected subgraph problem on undirected graphs. Finally, we study the problem for general crossing supermodular functions and show the following bi-criteria approximation result. Let k denote the maximum requirement of any set under the given requirement function f. We give 2k-approximation algorithm to construct a solution that satisfies a slightly weaker requirement function, namely, f\u27(S) = max{f(S) - 1,0}
Approximation Algorithms for (S,T)-Connectivity Problems
We study a directed network design problem called the --connectivity problem; we design and analyze approximation
algorithms and give hardness results. For each positive integer , the minimum cost -vertex connected spanning subgraph problem is a special case of the --connectivity problem. We defer
precise statements of the problem and of our results to the introduction.
For , we call the problem the -connectivity problem. We study three variants of the problem: the standard
-connectivity problem, the relaxed -connectivity problem, and the unrestricted -connectivity problem. We give hardness results for these three variants. We design a -approximation algorithm for the standard -connectivity problem. We design tight approximation algorithms for the relaxed -connectivity problem and one of its special cases.
For any , we give an -approximation algorithm,
where denotes the number of vertices. The approximation guarantee
almost matches the best approximation guarantee known for the minimum
cost -vertex connected spanning subgraph problem which is due to Nutov in 2009
Approximating Airports and Railways
In this paper we consider the airport and railway problem (AR), which combines capacitated facility location with network design, both in the general metric and the two-dimensional Euclidean space. An instance of the airport and railway problem consists of a set of points in the corresponding metric, together with a non-negative weight for each point, and a parameter k. The points represent cities, the weights denote costs of opening an airport in the corresponding city, and the parameter k is a maximum capacity of an airport. The goal is to construct a minimum cost network of airports and railways connecting all the cities, where railways correspond to edges connecting pairs of points, and the cost of a railway is equal to the distance between the corresponding points. The network is partitioned into components, where each component contains an open airport, and spans at most k cities. For the Euclidean case, any points in the plane can be used as Steiner vertices of the network. We obtain the first bicriteria approximation algorithm for AR for the general metric case, which yields a 4-approximate solution with a resource augmentation of the airport capacity k by a factor of 2. More generally, for any parameter 0 < p <= 1 where pk is an integer we develop a (4/3)(2 + 1/p)-approximation algorithm for metric AR with a resource augmentation by a factor of 1 + p.
Furthermore, we obtain the first constant factor approximation algorithm that does not resort to resource augmentation for AR in the Euclidean plane. Additionally, for the Euclidean setting we provide a quasi-polynomial time approximation scheme for the same problem with a resource augmentation by a factor of 1 + mu on the airport capacity, for any fixed mu > 0
Approximation Algorithms for Flexible Graph Connectivity
We present approximation algorithms for several network design problems in
the model of Flexible Graph Connectivity (Adjiashvili, Hommelsheim and
M\"uhlenthaler, "Flexible Graph Connectivity", Math. Program. pp. 1-33 (2021),
and IPCO 2020: pp. 13-26).
Let , and be integers. In an instance of the
-Flexible Graph Connectivity problem, denoted -FGC, we have an
undirected connected graph , a partition of into a set of safe
edges and a set of unsafe edges , and nonnegative costs on
the edges. A subset of edges is feasible for the -FGC
problem if for any subset of unsafe edges with , the subgraph
is -edge connected. The algorithmic goal is to find a
feasible solution that minimizes . We present a
simple -approximation algorithm for the -FGC problem via a reduction
to the minimum-cost rooted -arborescence problem. This improves on the
-approximation algorithm of Adjiashvili et al. Our -approximation
algorithm for the -FGC problem extends to a -approximation
algorithm for the -FGC problem. We present a -approximation algorithm
for the -FGC problem, and an -approximation algorithm for
the -FGC problem. Finally, we improve on the result of Adjiashvili et
al. for the unweighted -FGC problem by presenting a
-approximation algorithm.
The -FGC problem is related to the well-known Capacitated
-Connected Subgraph problem (denoted Cap-k-ECSS) that arises in the area of
Capacitated Network Design. We give a -approximation
algorithm for the Cap-k-ECSS problem, where denotes the maximum
capacity of an edge.Comment: 23 pages, 1 figure, preliminary version in the Proceedings of the
41st IARCS Annual Conference on Foundations of Software Technology and
Theoretical Computer Science (FSTTCS 2021), December 15-17, (LIPIcs, Volume
213, Article No. 9, pp. 9:1-9:14), see
https://doi.org/10.4230/LIPIcs.FSTTCS.2021.9. Related manuscript:
arXiv:2102.0330
Improved Approximation Algorithms for Steiner Connectivity Augmentation Problems
The Weighted Connectivity Augmentation Problem is the problem of augmenting
the edge-connectivity of a given graph by adding links of minimum total cost.
This work focuses on connectivity augmentation problems in the Steiner setting,
where we are not interested in the connectivity between all nodes of the graph,
but only the connectivity between a specified subset of terminals.
We consider two related settings. In the Steiner Augmentation of a Graph
problem (-SAG), we are given a -edge-connected subgraph of a graph
. The goal is to augment by including links and nodes from of
minimum cost so that the edge-connectivity between nodes of increases by 1.
In the Steiner Connectivity Augmentation Problem (-SCAP), we are given a
Steiner -edge-connected graph connecting terminals , and we seek to add
links of minimum cost to create a Steiner -edge-connected graph for .
Note that -SAG is a special case of -SCAP.
All of the above problems can be approximated to within a factor of 2 using
e.g. Jain's iterative rounding algorithm for Survivable Network Design. In this
work, we leverage the framework of Traub and Zenklusen to give a -approximation for the Steiner Ring Augmentation Problem (SRAP):
given a cycle embedded in a larger graph and
a subset of terminals , choose a subset of links of minimum cost so that has 3 pairwise edge-disjoint paths
between every pair of terminals.
We show this yields a polynomial time algorithm with approximation ratio for -SCAP. We obtain an improved approximation
guarantee of for SRAP in the case that , which
yields a -approximation for -SAG for any
- …