11 Search Results for "Kendall, Graham"

Document
DOI: 10.4230/LIPIcs.CP.2025.37
Multi-League Sports Scheduling with Team Interdependencies: An Optimization Model

Authors: Nils Weidmann

Published in: LIPIcs, Volume 340, 31st International Conference on Principles and Practice of Constraint Programming (CP 2025)

Abstract
Every year, a large number of matches must be scheduled for professional and amateur sports teams. Several constraints have to be considered, including the overall capacity of venues and interdependencies between teams of the same club. As interdependent teams of a club play in different leagues, finding an optimal solution is very challenging for practitioners. While the problem of respecting capacity restrictions is well-addressed in prior work, interdependencies between teams are widely neglected, despite being a problem of major importance in practice. This paper enhances the formal definition of the multi-league-sports scheduling problem to take team interdependencies into account. We create an optimization problem to be solved by means of integer linear programming, and prove the corresponding decision problem to be NP-complete by a polynomial reduction from 3-SAT. An implementation which was used to schedule German table tennis leagues of a certain district demonstrates the practical applicability of the approach.
Cite as

Nils Weidmann. Multi-League Sports Scheduling with Team Interdependencies: An Optimization Model. In 31st International Conference on Principles and Practice of Constraint Programming (CP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 340, pp. 37:1-37:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{weidmann:LIPIcs.CP.2025.37,
  author =	{Weidmann, Nils},
  title =	{{Multi-League Sports Scheduling with Team Interdependencies: An Optimization Model}},
  booktitle =	{31st International Conference on Principles and Practice of Constraint Programming (CP 2025)},
  pages =	{37:1--37:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-380-5},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{340},
  editor =	{de la Banda, Maria Garcia},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2025.37},
  URN =		{urn:nbn:de:0030-drops-238986},
  doi =		{10.4230/LIPIcs.CP.2025.37},
  annote =	{Keywords: sports scheduling, linear optimization, constraint programming}
}
Document
DOI: 10.4230/OASIcs.SLATE.2025.8
An Architecture for Composite Combinatorial Optimization Solvers

Authors: Khalil Chrit, Jean-François Baffier, Pedro Patinho, and Salvador Abreu

Published in: OASIcs, Volume 135, 14th Symposium on Languages, Applications and Technologies (SLATE 2025)

Abstract
In this paper, we introduce elements for MoSCO, a framework for building hybrid metaheuristic-based solvers from a collection of reusable base components. The framework is implemented in Julia and provides a modular architecture for composing solvers through a pipeline-based approach. The modular design of MoSCO supports the creation of reusable components and adaptable solver strategies for various Constraint Satisfaction Problems (CSPs) and Constraint Optimization Problems (COPs). We validate MoSCO’s utility through practical examples, demonstrating its effectiveness in reconstructing established metaheuristics and enabling the creation of novel solver configurations. This work lays the foundation for future developments in automated solver construction and parameter optimization.
Cite as

Khalil Chrit, Jean-François Baffier, Pedro Patinho, and Salvador Abreu. An Architecture for Composite Combinatorial Optimization Solvers. In 14th Symposium on Languages, Applications and Technologies (SLATE 2025). Open Access Series in Informatics (OASIcs), Volume 135, pp. 8:1-8:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{chrit_et_al:OASIcs.SLATE.2025.8,
  author =	{Chrit, Khalil and Baffier, Jean-Fran\c{c}ois and Patinho, Pedro and Abreu, Salvador},
  title =	{{An Architecture for Composite Combinatorial Optimization Solvers}},
  booktitle =	{14th Symposium on Languages, Applications and Technologies (SLATE 2025)},
  pages =	{8:1--8:16},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-387-4},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{135},
  editor =	{Baptista, Jorge and Barateiro, Jos\'{e}},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2025.8},
  URN =		{urn:nbn:de:0030-drops-236885},
  doi =		{10.4230/OASIcs.SLATE.2025.8},
  annote =	{Keywords: Hybrid Metaheuristics, DSL}
}
Document
Track A: Algorithms, Complexity and Games
DOI: 10.4230/LIPIcs.ICALP.2025.104
Improved Approximation Algorithms for Three-Dimensional Bin Packing

Authors: Debajyoti Kar, Arindam Khan, and Malin Rau

Published in: LIPIcs, Volume 334, 52nd International Colloquium on Automata, Languages, and Programming (ICALP 2025)

Abstract
We study three fundamental three-dimensional (3D) geometric packing problems: 3D (Geometric) Bin Packing (3D-BP), 3D Strip Packing (3D-SP), and Minimum Volume Bounding Box (3D-MVBB), where given a set of 3D (rectangular) cuboids, the goal is to find an axis-aligned nonoverlapping packing of all cuboids. In 3D-BP, we need to pack the given cuboids into the minimum number of unit cube bins. In 3D-SP, we need to pack them into a 3D cuboid with a unit square base and minimum height. Finally, in 3D-MVBB, the goal is to pack into a cuboid box of minimum volume. It is NP-hard to even decide whether a set of rectangles can be packed into a unit square bin - giving an (absolute) approximation hardness of 2 for 3D-BP and 3D-SP. The previous best (absolute) approximation for all three problems is by Li and Cheng (SICOMP, 1990), who gave algorithms with approximation ratios of 13, 46/7, and 46/7+ε, respectively, for 3D-BP, 3D-SP, and 3D-MVBB. We provide improved approximation ratios of 6, 6, and 3+ε, respectively, for the three problems, for any constant ε > 0. For 3D-BP, in the asymptotic regime, Bansal, Correa, Kenyon, and Sviridenko (Math. Oper. Res., 2006) showed that there is no asymptotic polynomial-time approximation scheme (APTAS) even when all items have the same height. Caprara (Math. Oper. Res., 2008) gave an asymptotic approximation ratio of T_{∞}² + ε ≈ 2.86, where T_{∞} is the well-known Harmonic constant in Bin Packing. We provide an algorithm with an improved asymptotic approximation ratio of 3 T_{∞}/2 + ε ≈ 2.54. Further, we show that unlike 3D-BP (and 3D-SP), 3D-MVBB admits an APTAS.
Cite as

Debajyoti Kar, Arindam Khan, and Malin Rau. Improved Approximation Algorithms for Three-Dimensional Bin Packing. In 52nd International Colloquium on Automata, Languages, and Programming (ICALP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 334, pp. 104:1-104:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{kar_et_al:LIPIcs.ICALP.2025.104,
  author =	{Kar, Debajyoti and Khan, Arindam and Rau, Malin},
  title =	{{Improved Approximation Algorithms for Three-Dimensional Bin Packing}},
  booktitle =	{52nd International Colloquium on Automata, Languages, and Programming (ICALP 2025)},
  pages =	{104:1--104:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-372-0},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{334},
  editor =	{Censor-Hillel, Keren and Grandoni, Fabrizio and Ouaknine, Jo\"{e}l and Puppis, Gabriele},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2025.104},
  URN =		{urn:nbn:de:0030-drops-234814},
  doi =		{10.4230/LIPIcs.ICALP.2025.104},
  annote =	{Keywords: Approximation Algorithms, Geometric Packing, Multidimensional Packing}
}
Document
DOI: 10.4230/LIPIcs.OPODIS.2024.32
Distributed Agreement in the Arrovian Framework

Authors: Kenan Wood, Hammurabi Mendes, and Jonad Pulaj

Published in: LIPIcs, Volume 324, 28th International Conference on Principles of Distributed Systems (OPODIS 2024)

Abstract
Preference aggregation is a fundamental problem in voting theory, in which public input rankings of a set of alternatives (called preferences) must be aggregated into a single preference that satisfies certain soundness properties. The celebrated Arrow Impossibility Theorem is equivalent to a distributed task in a synchronous fault-free system that satisfies properties such as respecting unanimous preferences, maintaining independence of irrelevant alternatives (IIA), and non-dictatorship, along with consensus since only one preference can be decided. In this work, we study a weaker distributed task in which crash faults are introduced, IIA is not required, and the consensus property is relaxed to either k-set agreement or ε-approximate agreement using any metric on the set of preferences. In particular, we prove several novel impossibility results for both of these tasks in both synchronous and asynchronous distributed systems. We additionally show that the impossibility for our ε-approximate agreement task using the Kendall tau or Spearman footrule metrics holds under extremely weak assumptions.
Cite as

Kenan Wood, Hammurabi Mendes, and Jonad Pulaj. Distributed Agreement in the Arrovian Framework. In 28th International Conference on Principles of Distributed Systems (OPODIS 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 324, pp. 32:1-32:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{wood_et_al:LIPIcs.OPODIS.2024.32,
  author =	{Wood, Kenan and Mendes, Hammurabi and Pulaj, Jonad},
  title =	{{Distributed Agreement in the Arrovian Framework}},
  booktitle =	{28th International Conference on Principles of Distributed Systems (OPODIS 2024)},
  pages =	{32:1--32:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-360-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{324},
  editor =	{Bonomi, Silvia and Galletta, Letterio and Rivi\`{e}re, Etienne and Schiavoni, Valerio},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.OPODIS.2024.32},
  URN =		{urn:nbn:de:0030-drops-225686},
  doi =		{10.4230/LIPIcs.OPODIS.2024.32},
  annote =	{Keywords: Approximate Agreement, Set Agreement, Preference Aggregation, Voting Theory, Impossibility}
}
Document
Resource Paper
DOI: 10.4230/TGDK.2.2.5
The Reasonable Ontology Templates Framework

Authors: Martin Georg Skjæveland and Leif Harald Karlsen

Published in: TGDK, Volume 2, Issue 2 (2024): Special Issue on Resources for Graph Data and Knowledge. Transactions on Graph Data and Knowledge, Volume 2, Issue 2

Abstract
Reasonable Ontology Templates (OTTR) is a templating language for representing and instantiating patterns. It is based on simple and generic, but powerful, mechanisms such as recursive macro expansion, term substitution and type systems, and is designed particularly for building and maintaining RDF knowledge graphs and OWL ontologies. In this resource paper, we present the formal specifications that define the OTTR framework. This includes the fundamentals of the OTTR language and the adaptions to make it fit with standard semantic web languages, and two serialization formats developed for semantic web practitioners. We also present the OTTR framework’s support for documenting, publishing and managing template libraries, and for tools for practical bulk instantiation of templates from tabular data and queryable data sources. The functionality of the OTTR framework is available for use through Lutra, an open-source reference implementation, and other independent implementations. We report on the use and impact of OTTR by presenting selected industrial use cases. Finally, we reflect on some design considerations of the language and framework and present ideas for future work.
Cite as

Martin Georg Skjæveland and Leif Harald Karlsen. The Reasonable Ontology Templates Framework. In Special Issue on Resources for Graph Data and Knowledge. Transactions on Graph Data and Knowledge (TGDK), Volume 2, Issue 2, pp. 5:1-5:54, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@Article{skjaeveland_et_al:TGDK.2.2.5,
  author =	{Skj{\ae}veland, Martin Georg and Karlsen, Leif Harald},
  title =	{{The Reasonable Ontology Templates Framework}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{5:1--5:54},
  ISSN =	{2942-7517},
  year =	{2024},
  volume =	{2},
  number =	{2},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.2.2.5},
  URN =		{urn:nbn:de:0030-drops-225896},
  doi =		{10.4230/TGDK.2.2.5},
  annote =	{Keywords: Ontology engineering, Ontology design patterns, Template mechanism, Macros}
}
Document
Vision
DOI: 10.4230/TGDK.1.1.3
Knowledge Engineering Using Large Language Models

Authors: Bradley P. Allen, Lise Stork, and Paul Groth

Published in: TGDK, Volume 1, Issue 1 (2023): Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge, Volume 1, Issue 1

Abstract
Knowledge engineering is a discipline that focuses on the creation and maintenance of processes that generate and apply knowledge. Traditionally, knowledge engineering approaches have focused on knowledge expressed in formal languages. The emergence of large language models and their capabilities to effectively work with natural language, in its broadest sense, raises questions about the foundations and practice of knowledge engineering. Here, we outline the potential role of LLMs in knowledge engineering, identifying two central directions: 1) creating hybrid neuro-symbolic knowledge systems; and 2) enabling knowledge engineering in natural language. Additionally, we formulate key open research questions to tackle these directions.
Cite as

Bradley P. Allen, Lise Stork, and Paul Groth. Knowledge Engineering Using Large Language Models. In Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge (TGDK), Volume 1, Issue 1, pp. 3:1-3:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{allen_et_al:TGDK.1.1.3,
  author =	{Allen, Bradley P. and Stork, Lise and Groth, Paul},
  title =	{{Knowledge Engineering Using Large Language Models}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{3:1--3:19},
  ISSN =	{2942-7517},
  year =	{2023},
  volume =	{1},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.1.1.3},
  URN =		{urn:nbn:de:0030-drops-194777},
  doi =		{10.4230/TGDK.1.1.3},
  annote =	{Keywords: knowledge engineering, large language models}
}
Document
DOI: 10.4230/DFU.Vol6.12191.33
Learning and Game AI

Authors: Hector Muñoz-Avila, Christian Bauckhage, Michal Bida, Clare Bates Congdon, and Graham Kendall

Published in: Dagstuhl Follow-Ups, Volume 6, Artificial and Computational Intelligence in Games (2013)

Abstract
The incorporation of learning into commercial games can enrich the player experience, but may concern developers in terms of issues such as losing control of their game world. We explore a number of applied research and some fielded applications that point to the tremendous possibilities of machine learning research including game genres such as real-time strategy games, flight simulation games, car and motorcycle racing games, board games such as Go, an even traditional game-theoretic problems such as the prisoners dilemma. A common trait of these works is the potential of machine learning to reduce the burden of game developers. However a number of challenges exists that hinder the use of machine learning more broadly. We discuss some of these challenges while at the same time exploring opportunities for a wide use of machine learning in games.
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Hector Muñoz-Avila, Christian Bauckhage, Michal Bida, Clare Bates Congdon, and Graham Kendall. Learning and Game AI. In Artificial and Computational Intelligence in Games. Dagstuhl Follow-Ups, Volume 6, pp. 33-43, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2013)

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@InCollection{munozavila_et_al:DFU.Vol6.12191.33,
  author =	{Mu\~{n}oz-Avila, Hector and Bauckhage, Christian and Bida, Michal and Congdon, Clare Bates and Kendall, Graham},
  title =	{{Learning and Game AI}},
  booktitle =	{Artificial and Computational Intelligence in Games},
  pages =	{33--43},
  series =	{Dagstuhl Follow-Ups},
  ISBN =	{978-3-939897-62-0},
  ISSN =	{1868-8977},
  year =	{2013},
  volume =	{6},
  editor =	{Lucas, Simon M. and Mateas, Michael and Preuss, Mike and Spronck, Pieter and Togelius, Julian},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DFU.Vol6.12191.33},
  URN =		{urn:nbn:de:0030-drops-43348},
  doi =		{10.4230/DFU.Vol6.12191.33},
  annote =	{Keywords: Games, machine learning, artificial intelligence, computational intelligence}
}
Document
DOI: 10.4230/DFU.Vol6.12191.77
General Video Game Playing

Authors: John Levine, Clare Bates Congdon, Marc Ebner, Graham Kendall, Simon M. Lucas, Risto Miikkulainen, Tom Schaul, and Tommy Thompson

Published in: Dagstuhl Follow-Ups, Volume 6, Artificial and Computational Intelligence in Games (2013)

Abstract
One of the grand challenges of AI is to create general intelligence: an agent that can excel at many tasks, not just one. In the area of games, this has given rise to the challenge of General Game Playing (GGP). In GGP, the game (typically a turn-taking board game) is defined declaratively in terms of the logic of the game (what happens when a move is made, how the scoring system works, how the winner is declared, and so on). The AI player then has to work out how to play the game and how to win. In this work, we seek to extend the idea of General Game Playing into the realm of video games, thus forming the area of General Video Game Playing (GVGP). In GVGP, computational agents will be asked to play video games that they have not seen before. At the minimum, the agent will be given the current state of the world and told what actions are applicable. Every game tick the agent will have to decide on its action, and the state will be updated, taking into account the actions of the other agents in the game and the game physics. We envisage running a competition based on GVGP playing, using arcadestyle (e.g. similar to Atari 2600) games as our starting point. These games are rich enough to be a formidable challenge to a GVGP agent, without introducing unnecessary complexity. The competition that we envisage could have a number of tracks, based on the form of the state (frame buffer or object model) and whether or not a forward model of action execution is available. We propose that the existing Physical Travelling Salesman (PTSP) software could be extended for our purposes and that a variety of GVGP games could be created in this framework by AI and Games students and other developers. Beyond this, we envisage the development of a Video Game Description Language (VGDL) as a way of concisely specifying video games. For the competition, we see this as being an interesting challenge in terms of deliberative search, machine learning and transfer of existing knowledge into new domains.
Cite as

John Levine, Clare Bates Congdon, Marc Ebner, Graham Kendall, Simon M. Lucas, Risto Miikkulainen, Tom Schaul, and Tommy Thompson. General Video Game Playing. In Artificial and Computational Intelligence in Games. Dagstuhl Follow-Ups, Volume 6, pp. 77-83, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2013)

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@InCollection{levine_et_al:DFU.Vol6.12191.77,
  author =	{Levine, John and Congdon, Clare Bates and Ebner, Marc and Kendall, Graham and Lucas, Simon M. and Miikkulainen, Risto and Schaul, Tom and Thompson, Tommy},
  title =	{{General Video Game Playing}},
  booktitle =	{Artificial and Computational Intelligence in Games},
  pages =	{77--83},
  series =	{Dagstuhl Follow-Ups},
  ISBN =	{978-3-939897-62-0},
  ISSN =	{1868-8977},
  year =	{2013},
  volume =	{6},
  editor =	{Lucas, Simon M. and Mateas, Michael and Preuss, Mike and Spronck, Pieter and Togelius, Julian},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DFU.Vol6.12191.77},
  URN =		{urn:nbn:de:0030-drops-43374},
  doi =		{10.4230/DFU.Vol6.12191.77},
  annote =	{Keywords: Video games, artificial intelligence, artificial general intelligence}
}
Document
DOI: 10.4230/DFU.Vol6.12191.101
Artificial and Computational Intelligence for Games on Mobile Platforms

Authors: Clare Bates Congdon, Philip Hingston, and Graham Kendall

Published in: Dagstuhl Follow-Ups, Volume 6, Artificial and Computational Intelligence in Games (2013)

Abstract
In this chapter, we consider the possibilities of creating new and innovative games that are targeted for mobile devices, such as smart phones and tablets, and that showcase AI (Artificial Intelligence) and CI (Computational Intelligence) approaches. Such games might take advantage of the sensors and facilities that are not available on other platforms, or might simply rely on the "app culture" to facilitate getting the games into users' hands. While these games might be profitable in themselves, our focus is on the benefits and challenges of developing AI and CI games for mobile devices.
Cite as

Clare Bates Congdon, Philip Hingston, and Graham Kendall. Artificial and Computational Intelligence for Games on Mobile Platforms. In Artificial and Computational Intelligence in Games. Dagstuhl Follow-Ups, Volume 6, pp. 101-108, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2013)

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@InCollection{congdon_et_al:DFU.Vol6.12191.101,
  author =	{Congdon, Clare Bates and Hingston, Philip and Kendall, Graham},
  title =	{{Artificial and Computational Intelligence for Games on Mobile Platforms}},
  booktitle =	{Artificial and Computational Intelligence in Games},
  pages =	{101--108},
  series =	{Dagstuhl Follow-Ups},
  ISBN =	{978-3-939897-62-0},
  ISSN =	{1868-8977},
  year =	{2013},
  volume =	{6},
  editor =	{Lucas, Simon M. and Mateas, Michael and Preuss, Mike and Spronck, Pieter and Togelius, Julian},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DFU.Vol6.12191.101},
  URN =		{urn:nbn:de:0030-drops-43393},
  doi =		{10.4230/DFU.Vol6.12191.101},
  annote =	{Keywords: Games, mobile, artificial intelligence, computational intelligence}
}
Document
DOI: 10.4230/DagSemProc.07112.1
07112 Abstracts Collection – Cutting, Packing, Layout and Space Allocation

Authors: Edmund Burke, Karen M. Daniels, and Graham Kendall

Published in: Dagstuhl Seminar Proceedings, Volume 7112, Cutting, Packing, Layout and Space Allocation (2007)

Abstract
From 13.03. to 16.03.2007, the Dagstuhl Seminar 07112 ``Cutting, Packing, Layout and Space Allocation'' was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available.
Cite as

Edmund Burke, Karen M. Daniels, and Graham Kendall. 07112 Abstracts Collection – Cutting, Packing, Layout and Space Allocation. In Cutting, Packing, Layout and Space Allocation. Dagstuhl Seminar Proceedings, Volume 7112, pp. 1-6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2007)

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@InProceedings{burke_et_al:DagSemProc.07112.1,
  author =	{Burke, Edmund and Daniels, Karen M. and Kendall, Graham},
  title =	{{07112 Abstracts Collection – Cutting, Packing, Layout and Space Allocation}},
  booktitle =	{Cutting, Packing, Layout and Space Allocation},
  pages =	{1--6},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2007},
  volume =	{7112},
  editor =	{Edmund Burke and Karen M. Daniels and Graham Kendall},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.07112.1},
  URN =		{urn:nbn:de:0030-drops-12880},
  doi =		{10.4230/DagSemProc.07112.1},
  annote =	{Keywords: Cutting and Packing, Nesting, Space Allocation, Layout, Optimisation}
}
Document
DOI: 10.4230/DagSemProc.07112.2
07112 Summary – Cutting, Packing, Layout and Space Allocation

Authors: Edmund Burke, Karen M. Daniels, and Graham Kendall

Published in: Dagstuhl Seminar Proceedings, Volume 7112, Cutting, Packing, Layout and Space Allocation (2007)

Abstract
Dagstuhl Seminar 07112 took place from Wednesday, 14th March, 2007 to Friday, 16th March. There were 17 participants from a total of 9 different countries. The seminar was led by Graham Kendall and Karen Daniels. Jan van der Veen was designated to collate the proceedings.
Cite as

Edmund Burke, Karen M. Daniels, and Graham Kendall. 07112 Summary – Cutting, Packing, Layout and Space Allocation. In Cutting, Packing, Layout and Space Allocation. Dagstuhl Seminar Proceedings, Volume 7112, pp. 1-3, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2007)

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@InProceedings{burke_et_al:DagSemProc.07112.2,
  author =	{Burke, Edmund and Daniels, Karen M. and Kendall, Graham},
  title =	{{07112 Summary – Cutting, Packing, Layout and Space Allocation}},
  booktitle =	{Cutting, Packing, Layout and Space Allocation},
  pages =	{1--3},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2007},
  volume =	{7112},
  editor =	{Edmund Burke and Karen M. Daniels and Graham Kendall},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.07112.2},
  URN =		{urn:nbn:de:0030-drops-12806},
  doi =		{10.4230/DagSemProc.07112.2},
  annote =	{Keywords: Cutting and Packing, Nesting, Space Allocation, Layout, Optimisation}
}
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