4,239 research outputs found
Deliver or hold: Approximation Algorithms for the Periodic Inventory Routing Problem
The inventory routing problem involves trading off inventory holding
costs at client locations with vehicle routing costs to deliver
frequently from a single central depot to meet deterministic client demands over a finite planing horizon. In this paper, we consider periodic solutions that visit clients in one of several specified frequencies, and focus on the case when the frequencies of visiting nodes are nested. We give the first constant-factor approximation algorithms for designing optimum nested periodic schedules for the problem with no limit on vehicle capacities by simple reductions to prize-collecting network design problems. For instance, we present a 2.55-approximation algorithm for the minimum-cost nested periodic
schedule where the vehicle routes are modeled as minimum Steiner trees. We also show a general reduction from the capacitated
problem where all vehicles have the same capacity to the uncapacitated
version with a slight loss in performance. This reduction gives a
4.55-approximation for the capacitated problem. In addition, we prove several structural results relating the values of optimal policies of various types
LP-Based Algorithms for Capacitated Facility Location
Linear programming has played a key role in the study of algorithms for
combinatorial optimization problems. In the field of approximation algorithms,
this is well illustrated by the uncapacitated facility location problem. A
variety of algorithmic methodologies, such as LP-rounding and primal-dual
method, have been applied to and evolved from algorithms for this problem.
Unfortunately, this collection of powerful algorithmic techniques had not yet
been applicable to the more general capacitated facility location problem. In
fact, all of the known algorithms with good performance guarantees were based
on a single technique, local search, and no linear programming relaxation was
known to efficiently approximate the problem.
In this paper, we present a linear programming relaxation with constant
integrality gap for capacitated facility location. We demonstrate that the
fundamental theories of multi-commodity flows and matchings provide key
insights that lead to the strong relaxation. Our algorithmic proof of
integrality gap is obtained by finally accessing the rich toolbox of LP-based
methodologies: we present a constant factor approximation algorithm based on
LP-rounding.Comment: 25 pages, 6 figures; minor revision
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
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
Approximating the generalized terminal backup problem via half-integral multiflow relaxation
We consider a network design problem called the generalized terminal backup
problem. Whereas earlier work investigated the edge-connectivity constraints
only, we consider both edge- and node-connectivity constraints for this
problem. A major contribution of this paper is the development of a strongly
polynomial-time 4/3-approximation algorithm for the problem. Specifically, we
show that a linear programming relaxation of the problem is half-integral, and
that the half-integral optimal solution can be rounded to a 4/3-approximate
solution. We also prove that the linear programming relaxation of the problem
with the edge-connectivity constraints is equivalent to minimizing the cost of
half-integral multiflows that satisfy flow demands given from terminals. This
observation presents a strongly polynomial-time algorithm for computing a
minimum cost half-integral multiflow under flow demand constraints
A simple dual ascent algorithm for the multilevel facility location problem
We present a simple dual ascent method for the multilevel facility location problem which finds a solution within times the optimum for the uncapacitated case and within times the optimum for the capacitated one. The algorithm is deterministic and based on the primal-dual technique. \u
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