Logic Based Methods For Optimization
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Logic Based Methods For Optimization
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Author : John Hooker
language : en
Publisher: John Wiley & Sons
Release Date : 2011-09-28
Logic Based Methods For Optimization written by John Hooker and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-28 with Mathematics categories.
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
Logic Based Methods For Optimization
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Author : John Hooker
language : en
Publisher: Wiley-Interscience
Release Date : 2000-05-30
Logic Based Methods For Optimization written by John Hooker and has been published by Wiley-Interscience this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-05-30 with Mathematics categories.
"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."--BOOK JACKET.
Optimization Methods For Logical Inference
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Author : Vijay Chandru
language : en
Publisher: John Wiley & Sons
Release Date : 2011-09-26
Optimization Methods For Logical Inference written by Vijay Chandru and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-26 with Mathematics categories.
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.
Fuzzy Logic Based In Optimization Methods And Control Systems And Its Applications
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Author : Ali Sadollah
language : en
Publisher: BoD – Books on Demand
Release Date : 2018-10-31
Fuzzy Logic Based In Optimization Methods And Control Systems And Its Applications written by Ali Sadollah and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-31 with Computers categories.
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.
Logic Synthesis And Optimization
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Author : Tsutomu Sasao
language : en
Publisher: Springer Science & Business Media
Release Date : 1993-01-31
Logic Synthesis And Optimization written by Tsutomu Sasao and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993-01-31 with Computers categories.
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.
Data Mining And Knowledge Discovery Via Logic Based Methods
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Author : Evangelos Triantaphyllou
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-06-08
Data Mining And Knowledge Discovery Via Logic Based Methods written by Evangelos Triantaphyllou and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-06-08 with Computers categories.
The importance of having ef cient and effective methods for data mining and kn- ledge discovery (DM&KD), to which the present book is devoted, grows every day and numerous such methods have been developed in recent decades. There exists a great variety of different settings for the main problem studied by data mining and knowledge discovery, and it seems that a very popular one is formulated in terms of binary attributes. In this setting, states of nature of the application area under consideration are described by Boolean vectors de ned on some attributes. That is, by data points de ned in the Boolean space of the attributes. It is postulated that there exists a partition of this space into two classes, which should be inferred as patterns on the attributes when only several data points are known, the so-called positive and negative training examples. The main problem in DM&KD is de ned as nding rules for recognizing (cl- sifying) new data points of unknown class, i. e. , deciding which of them are positive and which are negative. In other words, to infer the binary value of one more attribute, called the goal or class attribute. To solve this problem, some methods have been suggested which construct a Boolean function separating the two given sets of positive and negative training data points.
Logic Based 0 1 Constraint Programming
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Author : Peter Barth
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Logic Based 0 1 Constraint Programming written by Peter Barth and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Business & Economics categories.
A logic view of 0-1 integer programming problems, providing new insights into the structure of problems that can lead the researcher to more effective solution techniques depending on the problem class. Operations research techniques are integrated into a logic programming environment. The first monographic treatment that begins to unify these two methodological approaches. Logic-based methods for modelling and solving combinatorial problems have recently started to play a significant role in both theory and practice. The application of logic to combinatorial problems has a dual aspect. On one hand, constraint logic programming allows one to declaratively model combinatorial problems over an appropriate constraint domain, the problems then being solved by a corresponding constraint solver. Besides being a high-level declarative interface to the constraint solver, the logic programming language allows one also to implement those subproblems that cannot be naturally expressed with constraints. On the other hand, logic-based methods can be used as a constraint solving technique within a constraint solver for combinatorial problems modelled as 0-1 integer programs.
A New Meta Heuristic Optimization Algorithm Based On The String Theory Paradigm From Physics
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Author : Oscar Castillo
language : en
Publisher: Springer Nature
Release Date : 2021-08-18
A New Meta Heuristic Optimization Algorithm Based On The String Theory Paradigm From Physics written by Oscar Castillo and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-18 with Technology & Engineering categories.
This book focuses on the fields of nature-inspired algorithms, optimization problems and fuzzy logic. In this book, a new metaheuristic based on String Theory from Physics is proposed. It is important to mention that we have proposed the new algorithm to generate new potential solutions in optimization problems in order to find new ways that could improve the results in solving these problems. We are presenting the results for the proposed method in different cases of study. The first case, is optimization of traditional benchmark mathematical functions. The second case, is the optimization of benchmark functions of the CEC 2015 Competition and we are also presenting results of the CEC 2017 Competition on Constrained Real-Parameter Optimization that are problems that contain the presence of constraints that alter the shape of the search space making them more difficult to solve. Finally, in the third case, we are presenting the optimization of a fuzzy inference system, specifically for finding the optimal design of a fuzzy controller for an autonomous mobile robot. It is important to mention that in all study cases we are presenting statistical tests in or-der to validate the performance of proposed method. In summary, we believe that this book will be of great interest to a wide audience, ranging from engineering and science graduate students, to researchers and professors in computational intelligence, metaheuristics, optimization, robotics and control.
Principles And Practice Of Constraint Programming
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Author : Alan H. Borning
language : en
Publisher: Springer Science & Business Media
Release Date : 1994-10-12
Principles And Practice Of Constraint Programming written by Alan H. Borning and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994-10-12 with Computers categories.
This volume is the proceedings of the Second International Workshop on the Principles and Practice of Constraint Programming, held at Rosario, Orcas Island, Washington, USA in May 1994 in cooperation with AAAI and ALP. The volume contains 27 full revised papers selected from 87 submissions as well as a summary of a panel session on commercial applications of constraint programming. The contributions cover a broad range of topics including constraint programming languages, algorithms for constraint satisfaction and entailment, and constraints and their relation to fields such as artificial intelligence, databases, operations research, problem solving, and user interfaces.
Algorithms For Optimization
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Author : Mykel J. Kochenderfer
language : en
Publisher: MIT Press
Release Date : 2019-03-12
Algorithms For Optimization written by Mykel J. Kochenderfer and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-12 with Computers categories.
A comprehensive introduction to optimization with a focus on practical algorithms for the design of engineering systems. This book offers a comprehensive introduction to optimization with a focus on practical algorithms. The book approaches optimization from an engineering perspective, where the objective is to design a system that optimizes a set of metrics subject to constraints. Readers will learn about computational approaches for a range of challenges, including searching high-dimensional spaces, handling problems where there are multiple competing objectives, and accommodating uncertainty in the metrics. Figures, examples, and exercises convey the intuition behind the mathematical approaches. The text provides concrete implementations in the Julia programming language. Topics covered include derivatives and their generalization to multiple dimensions; local descent and first- and second-order methods that inform local descent; stochastic methods, which introduce randomness into the optimization process; linear constrained optimization, when both the objective function and the constraints are linear; surrogate models, probabilistic surrogate models, and using probabilistic surrogate models to guide optimization; optimization under uncertainty; uncertainty propagation; expression optimization; and multidisciplinary design optimization. Appendixes offer an introduction to the Julia language, test functions for evaluating algorithm performance, and mathematical concepts used in the derivation and analysis of the optimization methods discussed in the text. The book can be used by advanced undergraduates and graduate students in mathematics, statistics, computer science, any engineering field, (including electrical engineering and aerospace engineering), and operations research, and as a reference for professionals.