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Deep Statistical Comparison for Meta-heuristic Stochastic Optimization Algorithms

. Part II: Deep Statistical Comparison of meta-heuristic stochastic optimization algorithms - Chapters 5-7. Part III: Implementation and;

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Meta-heuristic and Evolutionary Algorithms for Engineering Optimization

optimization (ACO), and the particle swarm optimization (PSO) technique. Chapter 1 of Meta-heuristic and Evolutionary Algorithms for Engineering;

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A Framework for Alternation of Meta-Heuristic Algorithms

This work presents a new approach based on the alternation of meta-heuristic algorithms solving the problems of combinatorial optimization;

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Adaptive Stochastic Optimization Techniques with Applications

Adaptive Stochastic Optimization Techniques with Applications provides a single, convenient source for state-of-the-art information on;

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Dynamic Parameter Adaptation for Meta Heuristic Optimization Algorithms Through

In this book, a methodology for parameter adaptation in meta-heuristic op-timization methods is proposed. This methodology is based on;

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Optimization Models and Concepts in Production Management

Optimization techniques in production management are becoming increasingly important for efficient and competitive manufacturing. This book;

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Multimodal Optimization by Means of Evolutionary Algorithms

This book offers the first comprehensive taxonomy for multimodal optimization algorithms, work with its root in topics such as niching;

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Mathematical Geosciences

stochastic differential equation in Ito form. (2) Nature Inspired Global Optimization: Meta-heuristic algorithms are based on natural phenomenon such;

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Mathematical Foundations of Nature-Inspired Algorithms

of algorithms and understand how and why they work for solving optimization problems. In-depth mathematical analyses are carried out for different;

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Metaheuristics for Maritime Operations

and planning problems in both bulk and container shipping as well as liquid maritime transportation. Application of meta heuristic algorithm;

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Distributed Optimization Advances in Theories Methods and Applications

of distributed optimization in large-scale statistical learning, wireless sensor networks, and for optimal energy management in smart grids are discussed.;

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Distributed Optimization Advances in Theories Methods and Applications

of distributed optimization in large-scale statistical learning, wireless sensor networks, and for optimal energy management in smart grids are discussed.;

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Foundations of Computational Intelligence 03

(example: branch and bound methods), Stochastic optimization (example: simulated annealing). Heuristics and meta-heuristics (example: evolutionary;

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

problems can be modelled as multi-objective formulations. This book provides an introduction to multi-objective optimization using meta-heuristic;

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Classical and Recent Aspects of Power System Optimization

Classical and Recent Aspects of Power System Optimization presents conventional and meta-heuristic optimization methods and algorithms;

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Applications of Cuckoo Search Algorithm and its Variants

in medical and engineering applications. Evolutionary-based meta-heuristic approaches are increasingly being applied to solve complicated;

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Meta-Learning

questions: What is meta-learning?; why do we need meta-learning?; how are self-improved meta-learning mechanisms heading for AGI ?; how can we use;

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Nature-Inspired Methods for Metaheuristics Optimization

group of chapters describes in detail different meta-heuristic algorithms, and shows their applicability using some test or real-world problems;

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A Brief Introduction to Continuous Evolutionary Optimization

problem is available except via function evaluations. This work introduces a collection of heuristics and algorithms for black box optimization;

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Stochastic Global Optimization Methods and Applications to Chemical, Biochemical, Pharmaceutical and Environmental Processes

Stochastic global optimization methods and applications to chemical, biochemical, pharmaceutical and environmental processes presents;

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Simplicial Global Optimization

algorithms for global optimization and even use other non-rectangular partitions for special applications.;

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Introduction To Stochastic Search And Optimization

A unique interdisciplinary foundation for real-world problem solving Stochastic search and optimization techniques are used in a vast;

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Stochastic Recursive Algorithms for Optimization

Stochastic Recursive Algorithms for Optimization presents algorithms for constrained and unconstrained optimization and for reinforcement;

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Electromagnetic Optimization By Genetic Algorithms

Authoritative coverage of a revolutionary technique for overcoming problems in electromagnetic design Genetic algorithms are stochastic;

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Mean Field Simulation for Monte Carlo Integration

chain models, stochastic optimization, nonlinear filtering and multiple target tracking, stochastic optimization, calibration and uncertainty;

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Mean Field Simulation for Monte Carlo Integration

chain models, stochastic optimization, nonlinear filtering and multiple target tracking, stochastic optimization, calibration and uncertainty;

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Parallel Problem Solving from Nature -- PPSN XIV

, landscape-aware heuristic search, natural computing in scheduling and timetabling, and advances in multi-modal optimization. PPSN XIV also;

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