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Logic-Based Methods for Optimization

Author : John Hooker
Publisher : Wiley-Interscience
Page : 528 pages
File Size : 10,27 MB
Release : 2000-05-30
Category : Mathematics
ISBN :

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A pioneering look at the fundamental role of logic in optimization and constraint satisfaction While recent efforts to combine optimization and constraint satisfaction have received considerable attention, little has been said about using logic in optimization as the key to unifying the two fields. Logic-Based Methods for Optimization develops for the first time a comprehensive conceptual framework for integrating optimization and constraint satisfaction, then goes a step further and shows how extending logical inference to optimization allows for more powerful as well as flexible modeling and solution techniques. Designed to be easily accessible to industry professionals and academics in both operations research and artificial intelligence, the book provides a wealth of examples as well as elegant techniques and modeling frameworks ready for implementation. Timely, original, and thought-provoking, Logic-Based Methods for Optimization: * Demonstrates the advantages of combining the techniques in problem solving * Offers tutorials in constraint satisfaction/constraint programming and logical inference * Clearly explains such concepts as relaxation, cutting planes, nonserial dynamic programming, and Bender's decomposition * Reviews the necessary technologies for software developers seeking to combine the two techniques * Features extensive references to important computational studies * And much more

Logic-Based Methods for Optimization

Author : John Hooker
Publisher : John Wiley & Sons
Page : 520 pages
File Size : 32,29 MB
Release : 2011-09-28
Category : Mathematics
ISBN : 1118031288

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A pioneering look at the fundamental role of logic in optimizationand constraint satisfaction While recent efforts to combine optimization and constraintsatisfaction have received considerable attention, little has beensaid about using logic in optimization as the key to unifying thetwo fields. Logic-Based Methods for Optimization develops for thefirst time a comprehensive conceptual framework for integratingoptimization and constraint satisfaction, then goes a step furtherand shows how extending logical inference to optimization allowsfor more powerful as well as flexible modeling and solutiontechniques. Designed to be easily accessible to industryprofessionals and academics in both operations research andartificial intelligence, the book provides a wealth of examples aswell as elegant techniques and modeling frameworks ready forimplementation. Timely, original, and thought-provoking,Logic-Based Methods for Optimization: * Demonstrates the advantages of combining the techniques inproblem solving * Offers tutorials in constraint satisfaction/constraintprogramming and logical inference * Clearly explains such concepts as relaxation, cutting planes,nonserial dynamic programming, and Bender's decomposition * Reviews the necessary technologies for software developersseeking to combine the two techniques * Features extensive references to important computationalstudies * And much more

Fuzzy Logic Based in Optimization Methods and Control Systems and Its Applications

Author : Ali Sadollah
Publisher : BoD – Books on Demand
Page : 98 pages
File Size : 44,39 MB
Release : 2018-10-31
Category : Computers
ISBN : 1789840678

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Fuzzy logic models can be used to demonstrate human decision making in complex situations, and can therefore be an important tool in examining natural complexity. Moreover, fuzzy logic can be exploited to predict chaotic behaviors. But why is fuzzy logic so valuable? The idea of fuzzy logic has been around since 1965, and since its introduction thousands of applications of fuzzy logic have been implemented in industry, medicine, and even economic applications and patents. How did this invaluable theory achieve such great success? This book aims to compare well-known and well-used membership functions to demonstrate how to select the best membership functions and show when and why to utilize them. This book also demonstrates how different fields of studies utilize fuzzy logic showing its wide reach and relevance.

Optimization Methods for Logical Inference

Author : Vijay Chandru
Publisher : John Wiley & Sons
Page : 386 pages
File Size : 19,10 MB
Release : 2011-09-26
Category : Mathematics
ISBN : 1118031415

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Merging logic and mathematics in deductive inference-an innovative, cutting-edge approach. Optimization methods for logical inference? Absolutely, say Vijay Chandru and John Hooker, two major contributors to this rapidly expanding field. And even though "solving logical inference problems with optimization methods may seem a bit like eating sauerkraut with chopsticks. . . it is the mathematical structure of a problem that determines whether an optimization model can help solve it, not the context in which the problem occurs." Presenting powerful, proven optimization techniques for logic inference problems, Chandru and Hooker show how optimization models can be used not only to solve problems in artificial intelligence and mathematical programming, but also have tremendous application in complex systems in general. They survey most of the recent research from the past decade in logic/optimization interfaces, incorporate some of their own results, and emphasize the types of logic most receptive to optimization methods-propositional logic, first order predicate logic, probabilistic and related logics, logics that combine evidence such as Dempster-Shafer theory, rule systems with confidence factors, and constraint logic programming systems. Requiring no background in logic and clearly explaining all topics from the ground up, Optimization Methods for Logical Inference is an invaluable guide for scientists and students in diverse fields, including operations research, computer science, artificial intelligence, decision support systems, and engineering.

Logic Synthesis and Optimization

Author : Tsutomu Sasao
Publisher : Springer Science & Business Media
Page : 382 pages
File Size : 21,28 MB
Release : 2012-12-06
Category : Technology & Engineering
ISBN : 1461531543

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Logic Synthesis and Optimization presents up-to-date research information in a pedagogical form. The authors are recognized as the leading experts on the subject. The focus of the book is on logic minimization and includes such topics as two-level minimization, multi-level minimization, application of binary decision diagrams, delay optimization, asynchronous circuits, spectral method for logic design, field programmable gate array (FPGA) design, EXOR logic synthesis and technology mapping. Examples and illustrations are included so that each contribution can be read independently. Logic Synthesis and Optimization is an indispensable reference for academic researchers as well as professional CAD engineers.

Fuzzy Logic Hybrid Extensions of Neural and Optimization Algorithms: Theory and Applications

Author : Oscar Castillo
Publisher : Springer Nature
Page : 383 pages
File Size : 12,22 MB
Release : 2021-03-24
Category : Technology & Engineering
ISBN : 3030687767

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We describe in this book, recent developments on fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations, and their application in areas such as, intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction and optimization of complex problems. The book contains a collection of papers focused on hybrid intelligent systems based on soft computing. There are some papers with the main theme of type-1 and type-2 fuzzy logic, which basically consists of papers that propose new concepts and algorithms based on type-1 and type-2 fuzzy logic and their applications. There also some papers that presents theory and practice of meta-heuristics in different areas of application. Another group of papers describe diverse applications of fuzzy logic, neural networks and hybrid intelligent systems in medical applications. There are also some papers that present theory and practice of neural networks in different areas of application. In addition, there are papers that present theory and practice of optimization and evolutionary algorithms in different areas of application. Finally, there are some papers describing applications of fuzzy logic, neural networks and meta-heuristics in pattern recognition problems.

Logic Synthesis and Verification

Author : Soha Hassoun
Publisher : Springer Science & Business Media
Page : 474 pages
File Size : 17,6 MB
Release : 2001-11-30
Category : Computers
ISBN : 9780792376064

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Research and development of logic synthesis and verification have matured considerably over the past two decades. Many commercial products are available, and they have been critical in harnessing advances in fabrication technology to produce today's plethora of electronic components. While this maturity is assuring, the advances in fabrication continue to seemingly present unwieldy challenges. Logic Synthesis and Verification provides a state-of-the-art view of logic synthesis and verification. It consists of fifteen chapters, each focusing on a distinct aspect. Each chapter presents key developments, outlines future challenges, and lists essential references. Two unique features of this book are technical strength and comprehensiveness. The book chapters are written by twenty-eight recognized leaders in the field and reviewed by equally qualified experts. The topics collectively span the field. Logic Synthesis and Verification fills a current gap in the existing CAD literature. Each chapter contains essential information to study a topic at a great depth, and to understand further developments in the field. The book is intended for seniors, graduate students, researchers, and developers of related Computer-Aided Design (CAD) tools. From the foreword: "The commercial success of logic synthesis and verification is due in large part to the ideas of many of the authors of this book. Their innovative work contributed to design automation tools that permanently changed the course of electronic design." by Aart J. de Geus, Chairman and CEO, Synopsys, Inc.

Synthesis of Finite State Machines

Author : Tiziano Villa
Publisher : Springer Science & Business Media
Page : 382 pages
File Size : 50,71 MB
Release : 2012-12-06
Category : Technology & Engineering
ISBN : 1461561558

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Synthesis of Finite State Machines: Logic Optimization is the second in a set of two monographs devoted to the synthesis of Finite State Machines (FSMs). The first volume, Synthesis of Finite State Machines: Functional Optimization, addresses functional optimization, whereas this one addresses logic optimization. The result of functional optimization is a symbolic description of an FSM which represents a sequential function chosen from a collection of permissible candidates. Logic optimization is the body of techniques for converting a symbolic description of an FSM into a hardware implementation. The mapping of a given symbolic representation into a two-valued logic implementation is called state encoding (or state assignment) and it impacts heavily area, speed, testability and power consumption of the realized circuit. The first part of the book introduces the relevant background, presents results previously scattered in the literature on the computational complexity of encoding problems, and surveys in depth old and new approaches to encoding in logic synthesis. The second part of the book presents two main results about symbolic minimization; a new procedure to find minimal two-level symbolic covers, under face, dominance and disjunctive constraints, and a unified frame to check encodability of encoding constraints and find codes of minimum length that satisfy them. The third part of the book introduces generalized prime implicants (GPIs), which are the counterpart, in symbolic minimization of two-level logic, to prime implicants in two-valued two-level minimization. GPIs enable the design of an exact procedure for two-level symbolic minimization, based on a covering step which is complicated by the need to guarantee encodability of the final cover. A new efficient algorithm to verify encodability of a selected cover is presented. If a cover is not encodable, it is shown how to augment it minimally until an encodable superset of GPIs is determined. To handle encodability the authors have extended the frame to satisfy encoding constraints presented in the second part. The covering problems generated in the minimization of GPIs tend to be very large. Recently large covering problems have been attacked successfully by representing the covering table with binary decision diagrams (BDD). In the fourth part of the book the authors introduce such techniques and extend them to the case of the implicit minimization of GPIs, where the encodability and augmentation steps are also performed implicitly. Synthesis of Finite State Machines: Logic Optimization will be of interest to researchers and professional engineers who work in the area of computer-aided design of integrated circuits.