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Recent Advances in Computational Optimization

Overview of attention for book
Recent Advances in Computational Optimization
Springer International Publishing

Table of Contents

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    Book Overview
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    Chapter 1 Intuitionistic Fuzzy Logic as a Tool for Quality Assessment of Genetic Algorithms Performances
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    Chapter 2 A Graph Optimization Approach to Item-Based Collaborative Filtering
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    Chapter 3 Constraint Propagation for the Dial-a-Ride Problem with Split Loads
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    Chapter 4 ACO and GA for Parameter Settings of E. coli Fed-Batch Cultivation Model
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    Chapter 5 A Heuristic Based Algorithm for the 2D Circular Strip Packing Problem
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    Chapter 6 Experimental Evaluation of Pheromone Structures for Ant Colony Optimization: Application to the Robot Skin Wiring Problem
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    Chapter 7 Homogeneous Non Idling Problems: Models and Algorithms
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    Chapter 8 Flow Models for Project Scheduling with Transfer Delays and Financial Constraints
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    Chapter 9 A New Hybrid GA-FA Tuning of PID Controller for Glucose Concentration Control
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    Chapter 10 Some Properties of the Broyden Restricted Class of Updates with Oblique Projections
Attention for Chapter 1: Intuitionistic Fuzzy Logic as a Tool for Quality Assessment of Genetic Algorithms Performances
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Citations

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Chapter title
Intuitionistic Fuzzy Logic as a Tool for Quality Assessment of Genetic Algorithms Performances
Chapter number 1
Book title
Recent Advances in Computational Optimization
Published in
Studies in Computational Intelligence, January 2013
DOI 10.1007/978-3-319-00410-5_1
Book ISBNs
978-3-31-900409-9, 978-3-31-900410-5
Authors

Maria Angelova, Krassimir Atanassov, Tania Pencheva

Editors

Stefka Fidanova

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 1 100%
Readers by discipline Count As %
Chemical Engineering 1 100%

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