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Particle Swarm Optimization and Intelligence: Advances and Applications
"This book presents the most recent and established developments of Particle swarm optimization (PSO) within a unified framework by noted researchers in the field"--Provided by publisher.
Algorithm Portfolios
This book covers algorithm portfolios, multi-method schemes that harness optimization algorithms into a joint framework to solve optimization problems. It is expected to be a primary reference point for researchers and doctoral students in relevant domains that seek a quick exposure to the field. The presentation focuses primarily on the applicability of the methods and the non-expert reader will find this book useful for starting designing and implementing algorithm portfolios. The book familiarizes the reader with algorithm portfolios through current advances, applications, and open problems. Fundamental issues in building effective and efficient algorithm portfolios such as selection of constituent algorithms, allocation of computational resources, interaction between algorithms and parallelism vs. sequential implementations are discussed. Several new applications are analyzed and insights on the underlying algorithmic designs are provided. Future directions, new challenges, and open problems in the design of algorithm portfolios and applications are explored to further motivate research in this field.
Learning and Intelligent Optimization: Designing, Implementing and Analyzing Effective Heuristics
This book constitutes the thoroughly refereed post-conference proceedings of the Third International Conference on Learning and Intelligent Optimization, LION 2009 III, held in Trento, Italy, in January 2009. The 15 revised full papers, one extended abstract and two poster sessions were carefully reviewed and selected from 86 submissions for inclusion in the book. The papers cover current issues of stochastic local search methods and meta-heuristics, hybridizations of constraint and mathematical programming with meta-heuristics, supervised, unsupervised and reinforcement learning applied to heuristic search, reactive search (online self-tuning methods), algorithm portfolios and off-line tuni...
AI 2006: Advances in Artificial Intelligence
This book constitutes the refereed proceedings of the 19th Australian Joint Conference on Artificial Intelligence, AI 2006, held in Hobart, Australia, December 2006. Coverage includes foundations and knowledge based system, machine learning, connectionist AI, data mining, intelligent agents, cognition and user interface, vision and image processing, natural language processing and Web intelligence, neural networks, robotics, and AI applications.
Analysis of Experimental Algorithms
This book constitutes the refereed post-conference proceedings of the Special Event on the Analysis of Experimental Algorithms, SEA2 2019, held in Kalamata, Greece, in June 2019. The 35 revised full papers presented were carefully reviewed and selected from 45 submissions. The papers cover a wide range of topics in both computer science and operations research/mathematical programming. They focus on the role of experimentation and engineering techniques in the design and evaluation of algorithms, data structures, and computational optimization methods.
Parameter Setting in Evolutionary Algorithms
One of the main difficulties of applying an evolutionary algorithm (or, as a matter of fact, any heuristic method) to a given problem is to decide on an appropriate set of parameter values. Typically these are specified before the algorithm is run and include population size, selection rate, operator probabilities, not to mention the representation and the operators themselves. This book gives the reader a solid perspective on the different approaches that have been proposed to automate control of these parameters as well as understanding their interactions. The book covers a broad area of evolutionary computation, including genetic algorithms, evolution strategies, genetic programming, estimation of distribution algorithms, and also discusses the issues of specific parameters used in parallel implementations, multi-objective evolutionary algorithms, and practical consideration for real-world applications. It is a recommended read for researchers and practitioners of evolutionary computation and heuristic methods.
Metaheuristics for Finding Multiple Solutions
This book presents the latest trends and developments in multimodal optimization and niching techniques. Most existing optimization methods are designed for locating a single global solution. However, in real-world settings, many problems are “multimodal” by nature, i.e., multiple satisfactory solutions exist. It may be desirable to locate several such solutions before deciding which one to use. Multimodal optimization has been the subject of intense study in the field of population-based meta-heuristic algorithms, e.g., evolutionary algorithms (EAs), for the past few decades. These multimodal optimization techniques are commonly referred to as “niching” methods, because of the natur...
Open Problems in Optimization and Data Analysis
Computational and theoretical open problems in optimization, computational geometry, data science, logistics, statistics, supply chain modeling, and data analysis are examined in this book. Each contribution provides the fundamentals needed to fully comprehend the impact of individual problems. Current theoretical, algorithmic, and practical methods used to circumvent each problem are provided to stimulate a new effort towards innovative and efficient solutions. Aimed towards graduate students and researchers in mathematics, optimization, operations research, quantitative logistics, data analysis, and statistics, this book provides a broad comprehensive approach to understanding the significance of specific challenging or open problems within each discipline. The contributions contained in this book are based on lectures focused on “Challenges and Open Problems in Optimization and Data Science” presented at the Deucalion Summer Institute for Advanced Studies in Optimization, Mathematics, and Data Science in August 2016.
Control of Traffic Systems in Buildings
Transportation systems in buildings are part of everyday life: whether ferrying people twenty storeys up to the office or moving luggage at the airport, 21st-century society relies on them. This book presents the latest in analysis and control of transportation systems in buildings focusing primarily on elevator groups. The theory and design of passenger and cargo transport systems are covered, with operational examples and topics of special interest.
Applications of Evolutionary Computing
This book constitutes the refereed joint proceedings of six workshops on evolutionary computing, EvoWorkshops 2005, held in Lausanne, Switzerland in March/April 2005. The 56 revised full papers presented were carefully reviewed and selected from a total of 143 submissions. In accordance with the six workshops covered, the papers are organized in topical sections on evolutionary bioinformatics; evolutionary computing in communications, networks, and connected systems; hardware optimization techniques; evolutionary computation in image analysis and signal processing; evolutionary music and art; and evolutionary algorithms in stochastic and dynamic environments.
