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Handbook of Approximation Algorithms and Metaheuristics
Handbook of Approximation Algorithms and Metaheuristics, Second Edition reflects the tremendous growth in the field, over the past two decades. Through contributions from leading experts, this handbook provides a comprehensive introduction to the underlying theory and methodologies, as well as the various applications of approximation algorithms and metaheuristics. Volume 1 of this two-volume set deals primarily with methodologies and traditional applications. It includes restriction, relaxation, local ratio, approximation schemes, randomization, tabu search, evolutionary computation, local search, neural networks, and other metaheuristics. It also explores multi-objective optimization, reop...
Planning and Scheduling in Manufacturing and Services
This book focuses on planning and scheduling applications. Planning and scheduling are forms of decision-making that play an important role in most manufacturing and services industries. The planning and scheduling functions in a company typically use analytical techniques and heuristic methods to allocate its limited resources to the activities that have to be done. The application areas considered in this book are divided into manufacturing applications and services applications. The book covers five areas in manufacturing: project scheduling, job shop scheduling, scheduling of flexible assembly systems, economic lot scheduling, and planning and scheduling in supply chains. It covers four ...
Tuning Metaheuristics
This book lays the foundations for a scientific approach to tuning metaheuristics. The fundamental intuition that underlies Birattari's approach is that the tuning problem has much in common with the problems that are typically faced in machine learning.
Hybrid Metaheuristics
Optimization problems are of great importance in many fields. They can be tackled, for example, by approximate algorithms such as metaheuristics. Examples of metaheuristics are simulated annealing, tabu search, evolutionary computation, iterated local search, variable neighborhood search, and ant colony optimization. In recent years it has become evident that a skilled combination of a metaheuristic with other optimization techniques, a so called hybrid metaheuristic, can provide a more efficient behavior and a higher flexibility. This is because hybrid metaheuristics combine their advantages with the complementary strengths of, for example, more classical optimization techniques such as branch and bound or dynamic programming. The authors involved in this book are among the top researchers in their domain. The book is intended both to provide an overview of hybrid metaheuristics to novices of the field, and to provide researchers from the field with a collection of some of the most interesting recent developments.
ECAI 2006
In the summer of 1956, John McCarthy organized the famous Dartmouth Conference which is now commonly viewed as the founding event for the field of Artificial Intelligence. During the last 50 years, AI has seen a tremendous development and is now a well-established scientific discipline all over the world. Also in Europe AI is in excellent shape, as witnessed by the large number of high quality papers in this publication. In comparison with ECAI 2004, there's a strong increase in the relative number of submissions from Distributed AI/Agents and Cognitive Modelling. Knowledge Representation & Reasoning is traditionally strong in Europe and remains the biggest area of ECAI 2006. One reason the figures for Case-Based Reasoning are rather low is that much of the high quality work in this area has found its way into prestigious applications and is thus represented under the heading of PAIS.
Mathematical Reviews
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Discovery Science
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