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Evolutionary Computation 2020

Intelligent optimization is based on the mechanism of computational intelligence to refine a suitable feature model, design an effective optimization algorithm, and then to obtain an optimal or satisfactory solution to a complex problem. Intelligent algorithms are key tools to ensure global optimiza...

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Bibliographic Details
Main Author: Wang, Gai-Ge
Other Authors: Alavi, Amir
Format: eBook
Language:English
Published: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
Subjects:
Particle Swarm Optimization
Single Objective Optimization
Ant Colony Optimization
Turning-based Mutation
Multi-resources
Discrete Artificial Bee Colony Algorithm
Quantum
Engineering Optimization
Evolutionary Computation
Krill Herd
Dominance
Feature Selection
Game Trees
Mutation
Memetic Algorithm
Citation
Opposite Path
One-dimensional Inversions
Universities Ranking
Playtesting Metric
Magnetotelluric
Bwoa-s
Multi-task Optimization
Traveling Salesman Problems
Elephant Herding Optimization
Dynamic Learning
Path Discovery
Assortative Mating
Iterated Local Search
Swarm Intelligence
0-1 Knapsack Problem
Technology: General Issues / Bicssc
Multi-metric
Premature Convergence
Multi-indicators
Fuzzy Hybrid Flow Shop Scheduling
Geoelectric Model
Bwoa-v
Unified Search Space
Evolutionary Algorithm
Ranking
Multi-objective Optimization
Global Optimization
Self-adaptive Step Size
Woa
Differential Evolution
Many-objective Optimization
Knapsack Problem
Optimization Problem
Coevolution
Seed Schedule
Dimensionality Reduction
Multi-task Evolutionary Computation
Minimize Total Energy Consumption
Quantum Computing
Constrained Optimization
Playtesting
Game Feature
Grey Wolf Optimizer
H-index
Menu Planning Problem
Evolutionary Algorithms (eas)
Diversity Preservation
Opposition-based Learning
Q-learning
Decomposition-based Multi-objective Optimisation
Game Simulation
Simulated Annealing
Bug Detection
Single-objective Optimization
Classification
Whale Optimization Algorithm
Pareto Optimality
Knowledge Transfer
Cuckoo Search Algorithm
Performance Indicators
Green Shop Scheduling
Fuzzing
Validation
Binary Whale Optimization Algorithm
Minimize Makespan
Success-history
Metaheuristic
Travelling Salesman Problem
Pareto-front
Online Access:
Collection: Directory of Open Access Books - Collection details see MPG.ReNa
Description
Summary:Intelligent optimization is based on the mechanism of computational intelligence to refine a suitable feature model, design an effective optimization algorithm, and then to obtain an optimal or satisfactory solution to a complex problem. Intelligent algorithms are key tools to ensure global optimization quality, fast optimization efficiency and robust optimization performance. Intelligent optimization algorithms have been studied by many researchers, leading to improvements in the performance of algorithms such as the evolutionary algorithm, whale optimization algorithm, differential evolution algorithm, and particle swarm optimization. Studies in this arena have also resulted in breakthroughs in solving complex problems including the green shop scheduling problem, the severe nonlinear problem in one-dimensional geodesic electromagnetic inversion, error and bug finding problem in software, the 0-1 backpack problem, traveler problem, and logistics distribution center siting problem. The editors are confident that this book can open a new avenue for further improvement and discoveries in the area of intelligent algorithms. The book is a valuable resource for researchers interested in understanding the principles and design of intelligent algorithms.
Item Description:Creative Commons (cc), https://creativecommons.org/licenses/by/4.0/
Physical Description:1 electronic resource (442 p.)
ISBN:books978-3-0365-2395-8
9783036523958
9783036523941

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