5,780 research outputs found
Decompositions of Grammar Constraints
A wide range of constraints can be compactly specified using automata or
formal languages. In a sequence of recent papers, we have shown that an
effective means to reason with such specifications is to decompose them into
primitive constraints. We can then, for instance, use state of the art SAT
solvers and profit from their advanced features like fast unit propagation,
clause learning, and conflict-based search heuristics. This approach holds
promise for solving combinatorial problems in scheduling, rostering, and
configuration, as well as problems in more diverse areas like bioinformatics,
software testing and natural language processing. In addition, decomposition
may be an effective method to propagate other global constraints.Comment: Proceedings of the Twenty-Third AAAI Conference on Artificial
Intelligenc
Survey on Combinatorial Register Allocation and Instruction Scheduling
Register allocation (mapping variables to processor registers or memory) and
instruction scheduling (reordering instructions to increase instruction-level
parallelism) are essential tasks for generating efficient assembly code in a
compiler. In the last three decades, combinatorial optimization has emerged as
an alternative to traditional, heuristic algorithms for these two tasks.
Combinatorial optimization approaches can deliver optimal solutions according
to a model, can precisely capture trade-offs between conflicting decisions, and
are more flexible at the expense of increased compilation time.
This paper provides an exhaustive literature review and a classification of
combinatorial optimization approaches to register allocation and instruction
scheduling, with a focus on the techniques that are most applied in this
context: integer programming, constraint programming, partitioned Boolean
quadratic programming, and enumeration. Researchers in compilers and
combinatorial optimization can benefit from identifying developments, trends,
and challenges in the area; compiler practitioners may discern opportunities
and grasp the potential benefit of applying combinatorial optimization
A survey on constructing rosters for air traffic controllers
In this survey the state-of-the-art technology and the literature to date are discussed. In particular, we will discuss the gap in the literature concerning rostering staff to tasks by qualifications, with the inclusion of restrictions on a measure of task familiarity, which is a unique consequence of the structure of ATC operations
Temporal Data Modeling and Reasoning for Information Systems
Temporal knowledge representation and reasoning is a major research field in Artificial
Intelligence, in Database Systems, and in Web and Semantic Web research. The ability to
model and process time and calendar data is essential for many applications like appointment
scheduling, planning, Web services, temporal and active database systems, adaptive
Web applications, and mobile computing applications. This article aims at three complementary
goals. First, to provide with a general background in temporal data modeling
and reasoning approaches. Second, to serve as an orientation guide for further specific
reading. Third, to point to new application fields and research perspectives on temporal
knowledge representation and reasoning in the Web and Semantic Web
Dagstuhl Reports : Volume 1, Issue 2, February 2011
Online Privacy: Towards Informational Self-Determination on the Internet (Dagstuhl Perspectives Workshop 11061) : Simone Fischer-HĆ¼bner, Chris Hoofnagle, Kai Rannenberg, Michael Waidner, Ioannis Krontiris and Michael Marhƶfer Self-Repairing Programs (Dagstuhl Seminar 11062) : Mauro PezzĆ©, 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
Dagstuhl News January - December 2000
"Dagstuhl News" is a publication edited especially for the members of the Foundation "Informatikzentrum Schloss Dagstuhl" to thank them for their support. The News give a summary of the scientific work being done in Dagstuhl. Each Dagstuhl Seminar is presented by a small abstract describing the contents and scientific highlights of the seminar as well as the perspectives or challenges of the research topic
a(MDĆ)2: A Model Driven Approach to Multi-Dimensional Separation of Concerns with OCL
AbstractA typical activity in the object-oriented software engineering process involves the construction of a class structure in terms of which the system behaviour is to be specified. The behaviour, however, commonly consists of multiple tasks, each of which usually needs only part of the information available in that class structure. Additionally, a different representation of the required information may be appropriate. Therefore, it would be useful to be able to have multiple views on the global class structure, each being suitable for the specification of the behaviour related to a certain task. This paper introduces a(MDĆ)2, a technique to realise such a strategy. It incorporates OCL as a powerful query language and advocates a model driven development process which relieves the developer from the burden of manually writing a considerable amount of tedious and error-prone code
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