31,754 research outputs found
A reusable iterative optimization software library to solve combinatorial problems with approximate reasoning
Real world combinatorial optimization problems such as scheduling are
typically too complex to solve with exact methods. Additionally, the problems
often have to observe vaguely specified constraints of different importance,
the available data may be uncertain, and compromises between antagonistic
criteria may be necessary. We present a combination of approximate reasoning
based constraints and iterative optimization based heuristics that help to
model and solve such problems in a framework of C++ software libraries called
StarFLIP++. While initially developed to schedule continuous caster units in
steel plants, we present in this paper results from reusing the library
components in a shift scheduling system for the workforce of an industrial
production plant.Comment: 33 pages, 9 figures; for a project overview see
http://www.dbai.tuwien.ac.at/proj/StarFLIP
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Mapping genetic interactions in cancer: a road to rational combination therapies.
The discovery of synthetic lethal interactions between poly (ADP-ribose) polymerase (PARP) inhibitors and BRCA genes, which are involved in homologous recombination, led to the approval of PARP inhibition as a monotherapy for patients with BRCA1/2-mutated breast or ovarian cancer. Studies following the initial observation of synthetic lethality demonstrated that the reach of PARP inhibitors is well beyond just BRCA1/2 mutants. Insights into the mechanisms of action of anticancer drugs are fundamental for the development of targeted monotherapies or rational combination treatments that will synergize to promote cancer cell death and overcome mechanisms of resistance. The development of targeted therapeutic agents is premised on mapping the physical and functional dependencies of mutated genes in cancer. An important part of this effort is the systematic screening of genetic interactions in a variety of cancer types. Until recently, genetic-interaction screens have relied either on the pairwise perturbations of two genes or on the perturbation of genes of interest combined with inhibition by commonly used anticancer drugs. Here, we summarize recent advances in mapping genetic interactions using targeted, genome-wide, and high-throughput genetic screens, and we discuss the therapeutic insights obtained through such screens. We further focus on factors that should be considered in order to develop a robust analysis pipeline. Finally, we discuss the integration of functional interaction data with orthogonal methods and suggest that such approaches will increase the reach of genetic-interaction screens for the development of rational combination therapies
Dagstuhl Reports : Volume 1, Issue 2, February 2011
Online Privacy: Towards Informational Self-Determination on the Internet (Dagstuhl Perspectives Workshop 11061) : Simone Fischer-Hübner, Chris Hoofnagle, Kai Rannenberg, Michael Waidner, Ioannis Krontiris and Michael Marhöfer Self-Repairing Programs (Dagstuhl Seminar 11062) : Mauro Pezzé, Martin C. Rinard, Westley Weimer and Andreas Zeller Theory and Applications of Graph Searching Problems (Dagstuhl Seminar 11071) : Fedor V. Fomin, Pierre Fraigniaud, Stephan Kreutzer and Dimitrios M. Thilikos Combinatorial and Algorithmic Aspects of Sequence Processing (Dagstuhl Seminar 11081) : Maxime Crochemore, Lila Kari, Mehryar Mohri and Dirk Nowotka Packing and Scheduling Algorithms for Information and Communication Services (Dagstuhl Seminar 11091) Klaus Jansen, Claire Mathieu, Hadas Shachnai and Neal E. Youn
A Periodicity Metric for Assessing Maintenance Strategies
Organised by: Cranfield UniversityThe maintenance policy in manufacturing systems is devised to reset the machines functionality
in an economical fashion in order to keep the products quality within acceptable levels. Therefore,
there is a need for a metric to evaluate and quantify function resetting due to the adopted
maintenance policy. A novel metric for measuring the functional periodicity has been developed
using the complexity theory. It is based on the rate and extent of function resetting. It can be used
as an important criterion for comparing the different maintenance policy alternatives. An industrial
example is used to illustrate the application of the new metric.Mori Seiki – The Machine Tool Company; BAE Systems; S4T – Support Service Solutions: Strategy and Transitio
HFR Code: A Flexible Replication Scheme for Cloud Storage Systems
Fractional repetition (FR) codes are a family of repair-efficient storage
codes that provide exact and uncoded node repair at the minimum bandwidth
regenerating point. The advantageous repair properties are achieved by a
tailor-made two-layer encoding scheme which concatenates an outer
maximum-distance-separable (MDS) code and an inner repetition code. In this
paper, we generalize the application of FR codes and propose heterogeneous
fractional repetition (HFR) code, which is adaptable to the scenario where the
repetition degrees of coded packets are different. We provide explicit code
constructions by utilizing group divisible designs, which allow the design of
HFR codes over a large range of parameters. The constructed codes achieve the
system storage capacity under random access repair and have multiple repair
alternatives for node failures. Further, we take advantage of the systematic
feature of MDS codes and present a novel design framework of HFR codes, in
which storage nodes can be wisely partitioned into clusters such that data
reconstruction time can be reduced when contacting nodes in the same cluster.Comment: Accepted for publication in IET Communications, Jul. 201
Repairable Replication-based Storage Systems Using Resolvable Designs
We consider the design of regenerating codes for distributed storage systems
at the minimum bandwidth regeneration (MBR) point. The codes allow for a repair
process that is exact and uncoded, but table-based. These codes were introduced
in prior work and consist of an outer MDS code followed by an inner fractional
repetition (FR) code where copies of the coded symbols are placed on the
storage nodes. The main challenge in this domain is the design of the inner FR
code.
In our work, we consider generalizations of FR codes, by establishing their
connection with a family of combinatorial structures known as resolvable
designs. Our constructions based on affine geometries, Hadamard designs and
mutually orthogonal Latin squares allow the design of systems where a new node
can be exactly regenerated by downloading packets from a subset
of the surviving nodes (prior work only considered the case of ).
Our techniques allow the design of systems over a large range of parameters.
Specifically, the repetition degree of a symbol, which dictates the resilience
of the system can be varied over a large range in a simple manner. Moreover,
the actual table needed for the repair can also be implemented in a rather
straightforward way. Furthermore, we answer an open question posed in prior
work by demonstrating the existence of codes with parameters that are not
covered by Steiner systems
Unveiling combinatorial regulation through the combination of ChIP information and in silico cis-regulatory module detection
Computationally retrieving biologically relevant cis-regulatory modules (CRMs) is not straightforward. Because of the large number of candidates and the imperfection of the screening methods, many spurious CRMs are detected that are as high scoring as the biologically true ones. Using ChIP-information allows not only to reduce the regions in which the binding sites of the assayed transcription factor (TF) should be located, but also allows restricting the valid CRMs to those that contain the assayed TF (here referred to as applying CRM detection in a query-based mode). In this study, we show that exploiting ChIP-information in a query-based way makes in silico CRM detection a much more feasible endeavor. To be able to handle the large datasets, the query-based setting and other specificities proper to CRM detection on ChIP-Seq based data, we developed a novel powerful CRM detection method 'CPModule'. By applying it on a well-studied ChIP-Seq data set involved in self-renewal of mouse embryonic stem cells, we demonstrate how our tool can recover combinatorial regulation of five known TFs that are key in the self-renewal of mouse embryonic stem cells. Additionally, we make a number of new predictions on combinatorial regulation of these five key TFs with other TFs documented in TRANSFAC
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