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Application of Evolutionary Algorithms for Multi-objective Optimization in VLSI and Embedded Systems

utilized for solving multi-objective optimization problems in the area of embedded and VLSI system design. Many complex engineering optimization;

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Evolutionary Multi-Objective System Design

of the optimization process. Multi-objective optimization methods can be subdivided into classical and evolutionary. The classical methods;

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Evolutionary Multi-Objective System Design

-Objective System Design: Theory and Applications provides a representation of the state-of-the-art in evolutionary multi-objective optimization;

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Parallel Problem Solving from Nature -- PPSN XIV

optimization: why and how; evolutionary multi-objective optimization; intelligent systems for smart cities; advances on multi-modal optimization;

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Artificial Evolution

-evolution, artificial life, population dynamics, theory, algorithmic and modeling, implementations, application of evolutionary paradigms to the;

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Mathematical Optimization Terminology

of power distribution systems. It includes a short survey on model-based evolutionary algorithms and study on parameter optimization for support;

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Artificial Intelligence Algorithms and Applications

multi-objective and dynamic optimization, intelligent multimedia systems, virtualization and AI applications, smart scheduling, intelligent;

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Evolutionary Multi-Criterion Optimization

This book constitutes the refereed proceedings of the 11th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2021;

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Classical and Evolutionary Algorithms in the Optimization of Optical Systems

evolutionary algorithms and their application to the optimization of optical systems. This book, which is divided into four parts, illustrates the;

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Artificial Evolution

-evolution, artificial life, population dynamics, theory, algorithmics and modeling, implementations, application of evolutionary paradigms to the;

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Genetic Algorithms

latest issues and provides insights into various theoretical and technical aspects of evolutionary multi-objective optimization problems and;

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Archiving Strategies for Evolutionary Multi-objective Optimization Algorithms

of the sets of optimal and nearly optimal solutions of multi-objective optimization problems by means of stochastic search algorithms. All;

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Archiving Strategies for Evolutionary Multi objective Optimization Algorithms

of the sets of optimal and nearly optimal solutions of multi-objective optimization problems by means of stochastic search algorithms. All;

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Evolutionary Constrained Optimization

evolutionary algorithms. Broadly the topics covered include constraint handling for single and multi-objective optimizations; penalty function based;

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Nested algorithms for optimal reservoir operation and their embedding in a decision support platform

Reservoir operation is a multi-objective optimization problem, and is traditionally solved with dynamic programming (DP) and stochastic;

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Nested Algorithms for Optimal Reservoir Operation and Their Embedding in a Decision Support Platform

Reservoir operation is a multi-objective optimization problem, and is traditionally solved with dynamic programming (DP) and stochastic;

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Evolutionary Data Clustering

for data clustering. The book provides literature reviews about single objective and multi-objective evolutionary clustering algorithms;

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MultiObjective Optimization using Evolutionary Algorithms

Evolutionary algorithms are relatively new, but very powerful techniques used to find solutions to many real--world search and optimization;

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Multi-Objective Optimization Using Evolu

knowledge of multi-objective optimization and evolutionary algorithms Provides an extensive discussion on the principles of multi-objective;

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Advances in Swarm Intelligence, Part I

system, differential evolution, neural networks, genetic algorithms, evolutionary computation, fuzzy methods, and hybrid algorithms - for part I;

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Principles in Noisy Optimization

of evolutionary optimization, the book subsequently explores the principles of noisy optimization in single and multi-objective settings, and presents;

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Evolutionary Programming IV

in Evolutionary Computation.- Morphogenic Evolutionary Computation.- Issues in Evolutionary Optimization.- Evolutionary Applications to VLSI and Part;

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Evolutionary Computation

- and multi-objective optimization, and then goes on to discuss to explore applications of evolutionary algorithms for many uses with real-world;

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Evolutionary Computation

- and multi-objective optimization, and then goes on to discuss to explore applications of evolutionary algorithms for many uses with real-world;

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Advances in Swarm and Computational Intelligence

-based optimization algorithms and applications; particle swarm opt8imization; ant colony optimization; artificial bee colony algorithms;

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Advances in Swarm and Computational Intelligence

-based optimization algorithms and applications; particle swarm opt8imization; ant colony optimization; artificial bee colony algorithms;

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Advances in Swarm and Computational Intelligence

-based optimization algorithms and applications; particle swarm opt8imization; ant colony optimization; artificial bee colony algorithms;

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