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Books, Free Shipping, Optimization Techniques By Building Population-based Probabilistic Models From

Posted at: Offers to Sell and Export | Posted on: Mon 05 Jul, 2010 9:42 am | Product Category: Reference books [3760]
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Chapter 1 Fundamentals and Literature

1.1 Optimization Problems


Canonical Genetic Algorithm

1.3 Individual Representations

1.4 Mutation

1.5 Recombination

1.6 Population Models

1.7 Parent Selection

1.8 Survivor Selection

1.9 Summary

Chapter 2 The Probabilistic Model -building Genetic Algorithms

2.1 Introduction

2.2 A Simple Optimization Example

2.3 Different EDA Approaches

2.4 Optimization in Continuous Domains with EDAs

2.5 Summary

Chapter 3 An Empirical Comparison of EDAs in Binary Search Spaces

3.1 Introduction

3.2 Experiments

3.3 Test Functions for the Convergence Reliability

3.4 Experimental Results

3.5 Summary

Chapter 4 Development of a New Type of EDAs Based on Principle of Maximum Entropy

4.1 Introduction

4.2 Entropy and Schemata

4.3 The Idea of the Proposed Algorithms

4.4 How Can the Estimated Distribution be Computed and Sampled?

4.5 New Algorithms

4.6 Empirical Results

4.7 Summary

Chapter 5 Applying Continuous EDAs to Optimization Problems

5.1 Introduction

5.2 Description of the Optimization Problems

5.3 EDAs to Test

5.4 Experimental Description

5.5 Summary

Chapter 6 Optimizing Curriculum Scheduling Problem Using EDA

6.1 Introduction

6.2 Optimization Problem of Curriculum Scheduling

6.3 Methodology

6.4 Experimental Results

6.5 Summary

Chapter 7 Recognizing Human Brain Images Using EDAs

7.1 Introduction

7.2 Graph Matching Problem

7.3 Representing a Matching as a Permutation

7.4 Apply EDAs to Obtain a Permutation that Symbolizes the Solution

7.5 Obtaining a Permutation with Continuous EDAs

7.6 Experimental Results

7.7 Summary

Chapter 8 Optimizing Dynamic Pricing Problem with EDAs and GA

8.1 Introduction

8.2 Dynamic Pricing for Resource Management

8.3 Modeling Dynamic Pricing

8.4 An EA Approaches to Dynamic Pricing

8.5 Experiments and Results

8.6 Summary

Chapter 9 Improvement Techniques of EDAs

9.1 Introduction

9.2 Tradeoffs are Exploited by Efficiency-Improvement Techniques

9.3 Evaluation Relaxation: Designing Adaptive Endogenous Surrogates

9.4 Time Continuation: Mutation in EDAs

9.5 Summary

Product Details

Author Jiang Qun

Press Shanghai Jiaotong University Press

Isbn 9787313063694, 7313063695

Publication Date April 2010

Pages 156

Size 16K

Edition First

Cover Paperback

Language English

Page material gelatine plate paper

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