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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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A New Bio-inspired Optimization Algorithm Based on the Self-defense Mechanism of Plants in Nature

is used for dynamic parameter adaptation in the algorithm.;

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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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Fuzzy Logic Augmentation of Neural and Optimization Algorithms Theoretical Aspe

concepts and algorithms based on type-2 fuzzy logic for dynamic parameter adaptation in meta-heuristics. The second part discusses network theory;

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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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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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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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Self-Adaptive Heuristics For Evolutionary Computation

Evolutionary algorithms are successful biologically inspired meta-heuristics. Their success depends on adequate parameter settings. The;

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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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Evolutionary Constrained Optimization

; design of scalable test problems; parameter adaptation in constrained optimization; handling of integer, discrete and mix variables in addition;

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Adaptive Stochastic Optimization Techniques with Applications

optimization, decision analysis, intelligent systems, evolutionary programming, heuristic optimization, stochastic and adaptive dynamic programming;

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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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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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The Design of Approximation Algorithms

serve as a reference for researchers interested in the heuristic solution of discrete optimization problems.;

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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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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 New Meta-heuristic Optimization Algorithm Based on the String Theory Paradigm from Physics

for the proposed method in different cases of study. The first case, is optimization of traditional benchmark mathematical functions. The;

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Simulation-Based Optimization

dynamic simulation-based optimization. Covered in detail are model-free optimization techniques - especially designed for those discrete-event;

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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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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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Optimization Problems in Graph Theory

classes * A general technique for heuristic algorithms for optimization problems * The network design problem with cut constraints * Algorithms;

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Applications of Bat Algorithm and its Variants

application to find optimal solutions for a variety of real-world engineering and medical problems. Today, swarm intelligence-based meta-heuristic;

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Applications of Flower Pollination Algorithm and its Variants

find optimal solution for a variety of real-world engineering and medical problems. Swarm intelligence-based meta-heuristic algorithms are;

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Optimizing Engineering Problems through Heuristic Techniques

This book will cover heuristic optimization techniques and applications in engineering problems. The book will be divided into three;

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Optimizing Engineering Problems through Heuristic Techniques

This book will cover heuristic optimization techniques and applications in engineering problems. The book will be divided into three;

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Complex Scheduling

and genetic algorithms, and dynamic programming are presented. They are used in exact or heuristic procedures to solve the introduced complex;

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