THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

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Modern Applied Statistics With S

The field of metaheuristics for the application to combinatorial optimization problems is a rapidly growing field of research. This is due to the importance of combinatorial optimization problems for the scientific as well as the industrial world. We give a survey of the nowadays most important metaheuristics from a conceptual point of view. We outline the different components and concepts that are used in the different metaheuristics in order to analyze their similarities and differences. Two very important concepts in metaheuristics are intensification and diversification. These are the two forces that largely determine the behavior of a metaheuristic. They are in some way contrary but also complementary to each other. We introduce a framework, that we call the I&D frame, in order to put different intensification and diversification components into relation with each other. Outlining the advantages and disadvantages of different metaheuristic approaches we conclude by pointing out the importance of hybridization of metaheuristics as well as the integration of metaheuristics and other methods for optimization.

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Metaheuristics in combinatorial optimization: Overview and conceptual comparison

https://www.cs.ox.ac.uk/people/bernardo.cuencagrau/publications/PelletDemo.pdf

Pellet: A practical OWL-DL reasoner

A unified view of metaheuristics This book provides a complete background on metaheuristics and shows readers how to design and implement efficient algorithms to solve complex optimization problems across a diverse range of applications, from networking and bioinformatics to engineering design, routing, and scheduling. It presents the main design questions for all families of metaheuristics and clearly illustrates how to implement the algorithms under a software framework to reuse both the design and code. Throughout the book, the key search components of metaheuristics are considered as a toolbox for: Designing efficient metaheuristics (e.g. local search, tabu search, simulated annealing, evolutionary algorithms, particle swarm optimization, scatter search, ant colonies, bee colonies, artificial immune systems) for optimization problems Designing efficient metaheuristics for multi-objective optimization problems Designing hybrid, parallel, and distributed metaheuristics Implementing metaheuristics on sequential and parallel machines Using many case studies and treating design and implementation independently, this book gives readers the skills necessary to solve large-scale optimization problems quickly and efficiently. It is a valuable reference for practicing engineers and researchers from diverse areas dealing with optimization or machine learning; and graduate students in computer science, operations research, control, engineering, business and management, and applied mathematics.

/pdf/metaheuristics-from-design-to-implementation-1vqdfv8nk9.pdf

Metaheuristics: From Design to Implementation

The timetabling problem consists in scheduling a sequence of lectures between teachers and students in a prefixed period of time (typically a week), satisfying a set of constraints of various types. A large number of variants of the timetabling problem have been proposed in the literature, which differ from each other based on the type of institution involved (university or school) and the type of constraints. This problem, that has been traditionally considered in the operational research field, has recently been tackled with techniques belonging also to Artificial Intelligence (e.g., genetic algorithms, tabu search, and constraint satisfaction). In this paper, we survey the various formulations of the problem, and the techniques and algorithms used for its solution.

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A Survey of Automated Timetabling

Description Logics stem from Semantic Networks and Frames They deal with the representation of structured concepts and rea soning with them The structure of a concept is described using a language called concept language comprising boolean operators conjunction disjunction negation and various forms of quanti ca tion over the attributes or roles of the given concept A noticeable di erence with other structuring formalisms is that also roles can be given some internal structure e g a role can be expressed as a conjunction of two other roles We survey techniques for reasoning and computational complex ity of reasoning problems in Description Logics referring to four di erent settings reasoning with plain concept expressions! reasoning with instances of concepts! reasoning with axioms ex pressing properties of concepts! reasoning with both instances of concepts and axioms In the end of the paper we mention important aspects of De scription Logics not dealt within this survey

Reasoning in description logics

We present an integrated system for knowledge representation, called{\cal A}{\cal L} -log, based on description logics and the deductive database language Datalog. {\cal A}{\cal L}-log embodies two subsystems, called structural and relational. The former allows for the definition of structural knowledge about classes of interest (concepts) and membership relation between objects and classes. The latter allows for the definition of relational knowledge about objects described in the structural component. The interaction between the two components is obtained by allowing constraints within Datalog clauses, thus requiring the variables in the clauses to range over the set of instances of a specified concept. We propose a method for query answering in {\cal A}{\cal L}-log based on constrained resolution, where the usual deduction procedure defined for Datalog is integrated with a method for reasoning on the structural knowledge.

{\cal A}{\cal L} -log: Integrating Datalog and Description Logics

The EXAMINATION TIMETABLING problem regards the scheduling for the exams of a set of universitycourses, avoiding the overlapping of exams having students in common, fairlyspreading the exams for the students, and satisfying room capacity constraints.

We present a familyof solution algorithms for a set of variants of the EXAMINATION TIMETABLING problem. The algorithms are based on tabu search, and theyimp ort several features from the research on the GRAPH COLOURING problem.

Our algorithms are tested on both public benchmarks and random instances, and theyare compared with previous results in the literature. The comparison shows that the presented algorithms performs as well as constructive methods and memetic algorithms, and onlya decomposition based approach outperforms them in most cases.

Tabu Search Techniques for Examination Timetabling

The Second International Timetabling Competition (TTC2007) opened in August 2007. Building on the success of the first competition in 2002, this sequel aimed to further develop research activity in the area of educational timetabling. The broad aim of the competition was to create better understanding between researchers and practitioners by allowing emerging techniques to be developed and tested on real-world models of timetabling problems. To support this, a primary goal was to provide researchers with models of problems faced by practitioners through incorporating a significant number of real-world constraints. Another objective of the competition was to stimulate debate within the widening timetabling research community. The competition was divided into three tracks to reflect the important variations that exist in educational timetabling within higher education. Because these formulations incorporate an increased number of “real-world” issues, it is anticipated that the competition will now set the research agenda within the field. After finishing in January 2008, final results were made available in May 2008. Along with background to the competition, the competition tracks are described here along with a brief overview of the techniques used by the competition winners.

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Andrea Schaerf

Papers

A Survey of Automated Timetabling

Reasoning in description logics

{\cal A}{\cal L} -log: Integrating Datalog and Description Logics

Tabu Search Techniques for Examination Timetabling

Setting the Research Agenda in Automated Timetabling: The Second International Timetabling Competition