1,265 research outputs found
Robust Fault Tolerant uncapacitated facility location
In the uncapacitated facility location problem, given a graph, a set of
demands and opening costs, it is required to find a set of facilities R, so as
to minimize the sum of the cost of opening the facilities in R and the cost of
assigning all node demands to open facilities. This paper concerns the robust
fault-tolerant version of the uncapacitated facility location problem (RFTFL).
In this problem, one or more facilities might fail, and each demand should be
supplied by the closest open facility that did not fail. It is required to find
a set of facilities R, so as to minimize the sum of the cost of opening the
facilities in R and the cost of assigning all node demands to open facilities
that did not fail, after the failure of up to \alpha facilities. We present a
polynomial time algorithm that yields a 6.5-approximation for this problem with
at most one failure and a 1.5 + 7.5\alpha-approximation for the problem with at
most \alpha > 1 failures. We also show that the RFTFL problem is NP-hard even
on trees, and even in the case of a single failure
Improved approximation algorithm for k-level UFL with penalties, a simplistic view on randomizing the scaling parameter
The state of the art in approximation algorithms for facility location
problems are complicated combinations of various techniques. In particular, the
currently best 1.488-approximation algorithm for the uncapacitated facility
location (UFL) problem by Shi Li is presented as a result of a non-trivial
randomization of a certain scaling parameter in the LP-rounding algorithm by
Chudak and Shmoys combined with a primal-dual algorithm of Jain et al. In this
paper we first give a simple interpretation of this randomization process in
terms of solving an aux- iliary (factor revealing) LP. Then, armed with this
simple view point, Abstract. we exercise the randomization on a more
complicated algorithm for the k-level version of the problem with penalties in
which the planner has the option to pay a penalty instead of connecting chosen
clients, which results in an improved approximation algorithm
A heuristic approach for big bucket multi-level production planning problems
Multi-level production planning problems in which multiple items compete for the same resources frequently occur in practice, yet remain daunting in their difficulty to solve. In this paper, we propose a heuristic framework that can generate high quality feasible solutions quickly for various kinds of lot-sizing problems. In addition, unlike many other heuristics, it generates high quality lower bounds using strong formulations, and its simple scheme allows it to be easily implemented in the Xpress-Mosel modeling language. Extensive computational results from widely used test sets that include a variety of problems demonstrate the efficiency of the heuristic, particularly for challenging problems
A Lightweight Distributed Solution to Content Replication in Mobile Networks
Performance and reliability of content access in mobile networks is
conditioned by the number and location of content replicas deployed at the
network nodes. Facility location theory has been the traditional, centralized
approach to study content replication: computing the number and placement of
replicas in a network can be cast as an uncapacitated facility location
problem. The endeavour of this work is to design a distributed, lightweight
solution to the above joint optimization problem, while taking into account the
network dynamics. In particular, we devise a mechanism that lets nodes share
the burden of storing and providing content, so as to achieve load balancing,
and decide whether to replicate or drop the information so as to adapt to a
dynamic content demand and time-varying topology. We evaluate our mechanism
through simulation, by exploring a wide range of settings and studying
realistic content access mechanisms that go beyond the traditional
assumptionmatching demand points to their closest content replica. Results show
that our mechanism, which uses local measurements only, is: (i) extremely
precise in approximating an optimal solution to content placement and
replication; (ii) robust against network mobility; (iii) flexible in
accommodating various content access patterns, including variation in time and
space of the content demand.Comment: 12 page
Locating emergency services with priority rules: The priority queuing covering location problem
One of the assumptions of the Capacitated Facility Location Problem (CFLP) is that demand is known and fixed. Most often, this is not the case when managers take some strategic decisions such as locating facilities and assigning demand points to those facilities. In this paper we consider demand as stochastic and we model each of the facilities as an independent queue. Stochastic models of manufacturing systems and deterministic location models are put together in order to obtain a formula for the backlogging probability at a potential facility location. Several solution techniques have been proposed to solve the CFLP. One of the most recently proposed heuristics, a Reactive Greedy Adaptive Search Procedure, is implemented in order to solve the model formulated. We present some computational experiments in order to evaluate the heuristics’ performance and to illustrate the use of this new formulation for the CFLP. The paper finishes with a simple simulation exercise.Location, queuing, greedy heuristics, simulation
A computational analysis of lower bounds for big bucket production planning problems
In this paper, we analyze a variety of approaches to obtain lower bounds for multi-level production planning problems with big bucket capacities, i.e., problems in which multiple items compete for the same resources. We give an extensive survey of both known and new methods, and also establish relationships between some of these methods that, to our knowledge, have not been presented before. As will be highlighted, understanding the substructures of difficult problems provide crucial insights on why these problems are hard to solve, and this is addressed by a thorough analysis in the paper. We conclude with computational results on a variety of widely used test sets, and a discussion of future research
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