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Stochastic local search (SLS) algorithms are among the most prominent and successful techniques for solving computationally difficult problems in many areas of computer science and operations research, including propositional satisfiability, constraint satisfaction, routing, and scheduling. SLS algorithms have also become increasingly popular for solving challenging combinatorial problems in many application areas, such as e-commerce and bioinformatics.Hoos and Stützle offer the first systematic and unified treatment of SLS algorithms. In this groundbreaking new book, they examine the
Stochastic programming --- Algorithms --- Combinatorial analysis --- Programmation stochastique --- Algorithmes --- Analyse combinatoire --- 681.3*G13 --- Numerical linear algebra: conditioning; determinants; eigenvalues and eigenvectors; error analysis; linear systems; matrix inversion; pseudoinverses; singular value decomposition; sparse, structured, and very large systems (direct and iterative methods) --- Linear programming --- Combinatorics --- Algebra --- Mathematical analysis --- Algorism --- Arithmetic --- Foundations --- Algorithmes. --- Programmation stochastique. --- Analyse combinatoire. --- Algorithms. --- Combinatorial analysis. --- Stochastic programming.
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Mathematical logic --- Complex analysis --- Computer architecture. Operating systems --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- complexe analyse (wiskunde) --- wiskunde --- OS (operating system) --- logica --- robots --- numerieke analyse
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Complex analysis --- Computer science --- Information systems --- gegevensopslag --- cryptologie --- complexe analyse (wiskunde) --- programmeren (informatica) --- database management --- programmatielogica
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Stochastic local search (SLS) algorithms are among the most prominent and successful techniques for solving computationally difficult problems in many areas of computer science and operations research, including propositional satisfiability, constraint satisfaction, routing, and scheduling. SLS algorithms have also become increasingly popular for solving challenging combinatorial problems in many application areas, such as e-commerce and bioinformatics. Hoos and Stützle offer the first systematic and unified treatment of SLS algorithms. In this groundbreaking new book, they examine the general concepts and specific instances of SLS algorithms and carefully consider their development, analysis and application. The discussion focuses on the most successful SLS methods and explores their underlying principles, properties, and features. This book gives hands-on experience with some of the most widely used search techniques, and provides readers with the necessary understanding and skills to use this powerful tool. *Provides the first unified view of the field. *Offers an extensive review of state-of-the-art stochastic local search algorithms and their applications. *Presents and applies an advanced empirical methodology for analyzing the behavior of SLS algorithms. *A companion website offers lecture slides as well as source code and Java applets for exploring and demonstrating SLS algorithms.
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Propositional calculus --- Algebra, Boolean --- Computer algorithms --- Decision making --- Calcul propositionnel --- Algèbre de Boole --- Algorithmes --- Prise de décision --- Congresses. --- Congrès --- Mathematical Theory --- Mathematics --- Physical Sciences & Mathematics --- Boolean algebra --- Boole's algebra --- Calculus, Propositional --- Computer science. --- Operating systems (Computers). --- Algorithms. --- Mathematical logic. --- Numerical analysis. --- Artificial intelligence. --- Computer Science. --- Mathematical Logic and Formal Languages. --- Algorithm Analysis and Problem Complexity. --- Operating Systems. --- Numeric Computing. --- Artificial Intelligence (incl. Robotics). --- Mathematical Logic and Foundations. --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Mathematical analysis --- Algebra of logic --- Logic, Universal --- Mathematical logic --- Symbolic and mathematical logic --- Symbolic logic --- Algebra, Abstract --- Metamathematics --- Set theory --- Syllogism --- Algorism --- Algebra --- Arithmetic --- Computer operating systems --- Computers --- Disk operating systems --- Systems software --- Informatics --- Science --- Foundations --- Operating systems --- Algebraic logic --- Logic, Symbolic and mathematical --- Computer software. --- Electronic data processing. --- Logic, Symbolic and mathematical. --- Artificial Intelligence. --- ADP (Data processing) --- Automatic data processing --- Data processing --- EDP (Data processing) --- IDP (Data processing) --- Integrated data processing --- Office practice --- Software, Computer --- Computer systems --- Automation --- Propositional calculus - Congresses. --- Algebra, Boolean - Congresses. --- Computer algorithms - Congresses. --- Decision making - Congresses. --- Machine theory. --- Formal Languages and Automata Theory. --- Numerical Analysis. --- Abstract automata --- Abstract machines --- Automata --- Mathematical machine theory --- Algorithms --- Recursive functions --- Robotics
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Stochastic local search (SLS) algorithms enjoy great popularity as powerful and versatile tools for tackling computationally hard decision and optimization pr- lems from many areas of computer science, operations research, and engineering. To a large degree, this popularity is based on the conceptual simplicity of many SLS methods and on their excellent performance on a wide gamut of problems, ranging from rather abstract problems of high academic interest to the very s- ci?c problems encountered in many real-world applications. SLS methods range from quite simple construction procedures and iterative improvement algorithms to more complex general-purpose schemes, also widely known as metaheuristics, such as ant colony optimization, evolutionary computation, iterated local search, memetic algorithms, simulated annealing, tabu search and variable neighborhood search. Historically, the development of e?ective SLS algorithms has been guided to a large extent by experience and intuition, and overall resembled more an art than a science. However, in recent years it has become evident that at the core of this development task there is a highly complex engineering process, which combines various aspects of algorithm design with empirical analysis techniques and problem-speci?c background, and which relies heavily on knowledge from a number of disciplines and areas, including computer science, operations research, arti?cial intelligence, and statistics. This development process needs to be - sisted by a sound methodology that addresses the issues arising in the various phases of algorithm design, implementation, tuning, and experimental eval- tion.
Computer algorithms --- Electronic information resource searching --- Search theory --- Heuristic programming --- Stochastic programming --- Algorithmes --- Recherche de l'information électronique --- Programmation heuristique --- Congresses. --- Congrès --- Computer Science --- Engineering & Applied Sciences --- Computer searching --- Electronic searching --- Online searching --- Searching electronic information resources --- Computer science. --- Data structures (Computer science). --- Algorithms. --- Mathematical statistics. --- Data mining. --- Information storage and retrieval. --- Computer Science. --- Data Structures. --- Data Storage Representation. --- Algorithm Analysis and Problem Complexity. --- Probability and Statistics in Computer Science. --- Data Mining and Knowledge Discovery. --- Information Storage and Retrieval. --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Algorism --- Algebra --- Arithmetic --- Information structures (Computer science) --- Structures, Data (Computer science) --- Structures, Information (Computer science) --- Electronic data processing --- File organization (Computer science) --- Abstract data types (Computer science) --- Informatics --- Science --- Statistical methods --- Foundations --- Linear programming --- Operations research --- Artificial intelligence --- Programming (Mathematics) --- Information retrieval --- Data structures (Computer scienc. --- Computer software. --- Information storage and retrieva. --- Software, Computer --- Computer systems --- Information storage and retrieval systems. --- Automatic data storage --- Automatic information retrieval --- Automation in documentation --- Computer-based information systems --- Data processing systems --- Data storage and retrieval systems --- Discovery systems, Information --- Information discovery systems --- Information processing systems --- Information retrieval systems --- Machine data storage and retrieval --- Mechanized information storage and retrieval systems --- Electronic information resources --- Data libraries --- Digital libraries --- Information organization --- Artificial intelligence—Data processing. --- Information retrieval. --- Computer architecture. --- Computer science—Mathematics. --- Data Science. --- Data centers --- Architecture, Computer --- Data retrieval --- Data storage --- Discovery, Information --- Information discovery --- Information storage and retrieval --- Retrieval of information --- Documentation --- Information science --- Information storage and retrieval systems
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Stochastic local search (SLS) algorithms are established tools for the solution of computationally hard problems arising in computer science, business adm- istration, engineering, biology, and various other disciplines. To a large extent, their success is due to their conceptual simplicity, broad applicability and high performance for many important problems studied in academia and enco- tered in real-world applications. SLS methods include a wide spectrum of te- niques, ranging from constructive search procedures and iterative improvement algorithms to more complex SLS methods, such as ant colony optimization, evolutionary computation, iterated local search, memetic algorithms, simulated annealing, tabu search, and variable neighborhood search. Historically, the development of e?ective SLS algorithms has been guided to a large extent by experience and intuition. In recent years, it has become - creasingly evident that success with SLS algorithms depends not merely on the adoption and e?cient implementation of the most appropriate SLS technique for a given problem, but also on the mastery of a more complex algorithm - gineering process. Challenges in SLS algorithm development arise partly from the complexity of the problems being tackled and in part from the many - grees of freedom researchers and practitioners encounter when developing SLS algorithms. Crucial aspects in the SLS algorithm development comprise al- rithm design, empirical analysis techniques, problem-speci?c background, and background knowledge in several key disciplines and areas, including computer science, operations research, arti?cial intelligence, and statistics.
Computer algorithms --- Electronic information resource searching --- Search theory --- Heuristic programming --- Stochastic programming --- Computer Science --- Engineering & Applied Sciences --- Computer searching --- Electronic searching --- Online searching --- Searching electronic information resources --- Computer science. --- Computer programming. --- Data structures (Computer science). --- Algorithms. --- Computer logic. --- Computer Science. --- Programming Techniques. --- Data Structures. --- Data Structures, Cryptology and Information Theory. --- Data Storage Representation. --- Algorithm Analysis and Problem Complexity. --- Logics and Meanings of Programs. --- Computer science logic --- Logic, Symbolic and mathematical --- Algorism --- Algebra --- Arithmetic --- Information structures (Computer science) --- Structures, Data (Computer science) --- Structures, Information (Computer science) --- Electronic data processing --- File organization (Computer science) --- Abstract data types (Computer science) --- Computers --- Electronic computer programming --- Electronic digital computers --- Programming (Electronic computers) --- Coding theory --- Informatics --- Science --- Foundations --- Programming --- Linear programming --- Operations research --- Artificial intelligence --- Programming (Mathematics) --- Information retrieval --- Data structures (Computer scienc. --- Computer software. --- Logic design. --- Data Structures and Information Theory. --- Design, Logic --- Design of logic systems --- Digital electronics --- Electronic circuit design --- Logic circuits --- Machine theory --- Switching theory --- Software, Computer --- Computer systems --- Recursos electrònics en xarxa --- Cerca a Internet --- Programació estocàstica --- Programació lineal --- Cerca a la WEB --- Cerca per Internet --- Cerca web --- Recerca a Internet --- Recerca de la informació per Internet --- Internet --- Recuperació de la informació --- Cercadors d'Internet --- Alfabetització informacional --- Informació electrònica --- Recursos d'Internet --- Recursos en Internet --- Recursos en línia --- Recursos Web --- Recursos electrònics --- Canals de continguts (RSS) --- Catalogació de recursos electrònics en xarxa --- Llocs web --- Serveis electrònics de referència (Biblioteques) --- Artificial intelligence—Data processing. --- Information theory. --- Information retrieval. --- Computer architecture. --- Data Science. --- Computer Science Logic and Foundations of Programming. --- Architecture, Computer --- Data retrieval --- Data storage --- Discovery, Information --- Information discovery --- Information storage and retrieval --- Retrieval of information --- Documentation --- Information science --- Information storage and retrieval systems --- Communication theory --- Communication --- Cybernetics
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The 7th International Conference on Theory and Applications of Satis?ab- ity Testing (SAT 2004) was held 10-13 May 2004 in Vancouver, BC, Canada. The conference featured 9 technical paper sessions, 2 poster sessions, as well as the 2004 SAT Solver Competition and the 2004 QBF Solver Evaluation. It also included invited talks by Stephen A. Cook (University of Toronto) and Kenneth McMillan (Cadence Berkeley Labs). The 89 participants represented no less than 17 countries and four continents. SAT 2004 continued the series of meetings which started with the Workshops on Satis?ability held in Siena, Italy (1996), Paderborn, Germany (1998) and Renesse, The Netherlands (2000); the Workshop on Theory and Applications of Satis?ability Testing held in Boston, USA(2001);theSymposiumonTheoryandApplicationsofSatis?abilityTesting held in Cincinnati, USA (2002); and the 6th International Conference on Theory and Applications of Satis?ability Testing held in Santa Margherita Ligure, Italy (2003). The International Conference on Theory and Applications of Satis?ability Testing is the primary annual meeting for researchers studying the propo- tional satis?ability problem (SAT), a prominent problem in both theoretical and applied computer science. SAT lies at the heart of the most important open problem in complexity theory (P vsNP) and underlies many applications in, among other examples, arti?cial intelligence, operations research and electronic design engineering. The primary objective of the conferences is to bring together researchersfromvariousareasandcommunities,includingtheoreticalandexp- imental computer science as well as many relevant application areas, to promote collaboration and the communication of new theoretical and practical results in SAT-related research and its industrial applications.
Mathematical logic --- Complex analysis --- Computer architecture. Operating systems --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- complexe analyse (wiskunde) --- wiskunde --- OS (operating system) --- logica --- robots --- numerieke analyse
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