Lecture Notes in Computer Science - Learning and Intelligent Optimization
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Published By Springer International Publishing

9783319694030, 9783319694047

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A GRASP for the Minimum Cost SAT Problem

Lecture Notes in Computer Science - Learning and Intelligent Optimization ◽

10.1007/978-3-319-69404-7_5 ◽

2017 ◽

pp. 64-78

Author(s):

Giovanni Felici ◽

Daniele Ferone ◽

Paola Festa ◽

Antonio Napoletano ◽

Tommaso Pastore

Keyword(s):

Minimum Cost ◽

Sat Problem

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Global Optimization Challenges in Structured Low Rank Approximation

Lecture Notes in Computer Science - Learning and Intelligent Optimization ◽

10.1007/978-3-319-69404-7_26 ◽

2017 ◽

pp. 326-330

Author(s):

Jonathan Gillard ◽

Anatoly Zhigljavsky

Keyword(s):

Global Optimization ◽

Low Rank ◽

Low Rank Approximation ◽

Rank Approximation ◽

Structured Low Rank Approximation

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Interior Point and Newton Methods in Solving High Dimensional Flow Distribution Problems for Pipe Networks

Lecture Notes in Computer Science - Learning and Intelligent Optimization ◽

10.1007/978-3-319-69404-7_10 ◽

2017 ◽

pp. 139-149

Author(s):

Oleg O. Khamisov ◽

Valery A. Stennikov

Keyword(s):

Interior Point ◽

Flow Distribution ◽

High Dimensional ◽

Newton Methods ◽

Dimensional Flow ◽

Pipe Networks ◽

Distribution Problems

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Comparing Two Approaches for Solving Constrained Global Optimization Problems

Lecture Notes in Computer Science - Learning and Intelligent Optimization ◽

10.1007/978-3-319-69404-7_22 ◽

2017 ◽

pp. 301-306

Author(s):

Konstantin Barkalov ◽

Ilya Lebedev

Keyword(s):

Global Optimization ◽

Optimization Problems ◽

Constrained Global Optimization

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An Iterated Local Search Framework with Adaptive Operator Selection for Nurse Rostering

Lecture Notes in Computer Science - Learning and Intelligent Optimization ◽

10.1007/978-3-319-69404-7_7 ◽

2017 ◽

pp. 93-108 ◽

Cited By ~ 2

Author(s):

Angeliki Gretsista ◽

Edmund K. Burke

Keyword(s):

Local Search ◽

Iterated Local Search ◽

Nurse Rostering ◽

Adaptive Operator Selection ◽

Selection For

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Accelerating Gradient Descent with Projective Response Surface Methodology

Lecture Notes in Computer Science - Learning and Intelligent Optimization ◽

10.1007/978-3-319-69404-7_34 ◽

2017 ◽

pp. 376-382 ◽

Cited By ~ 2

Author(s):

Alexander Senov

Keyword(s):

Response Surface Methodology ◽

Response Surface ◽

Gradient Descent

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Efficient Adaptive Implementation of the Serial Schedule Generation Scheme Using Preprocessing and Bloom Filters

Lecture Notes in Computer Science - Learning and Intelligent Optimization ◽

10.1007/978-3-319-69404-7_9 ◽

2017 ◽

pp. 124-138

Author(s):

Daniel Karapetyan ◽

Alexei Vernitski

Keyword(s):

Bloom Filters

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Learning a Reactive Restart Strategy to Improve Stochastic Search

Lecture Notes in Computer Science - Learning and Intelligent Optimization ◽

10.1007/978-3-319-69404-7_8 ◽

2017 ◽

pp. 109-123 ◽

Cited By ~ 4

Author(s):

Serdar Kadioglu ◽

Meinolf Sellmann ◽

Markus Wagner

Keyword(s):

Stochastic Search ◽

Restart Strategy

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Solution of the Convergecast Scheduling Problem on a Square Unit Grid When the Transmission Range is 2

Lecture Notes in Computer Science - Learning and Intelligent Optimization ◽

10.1007/978-3-319-69404-7_4 ◽

2017 ◽

pp. 50-63 ◽

Cited By ~ 4

Author(s):

Adil Erzin

Keyword(s):

Transmission Range ◽

Scheduling Problem

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An Importance Sampling Approach to the Estimation of Algorithm Performance in Automated Algorithm Design

Lecture Notes in Computer Science - Learning and Intelligent Optimization ◽

10.1007/978-3-319-69404-7_1 ◽

2017 ◽

pp. 3-17 ◽

Cited By ~ 1

Author(s):

Steven Adriaensen ◽

Filip Moons ◽

Ann Nowé

Keyword(s):

Importance Sampling ◽

Algorithm Design ◽

Algorithm Performance ◽

Automated Algorithm ◽

Sampling Approach

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Lecture Notes in Computer Science - Learning and Intelligent OptimizationLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer International Publishing

A GRASP for the Minimum Cost SAT Problem

Global Optimization Challenges in Structured Low Rank Approximation

Interior Point and Newton Methods in Solving High Dimensional Flow Distribution Problems for Pipe Networks

Comparing Two Approaches for Solving Constrained Global Optimization Problems

An Iterated Local Search Framework with Adaptive Operator Selection for Nurse Rostering

Accelerating Gradient Descent with Projective Response Surface Methodology

Efficient Adaptive Implementation of the Serial Schedule Generation Scheme Using Preprocessing and Bloom Filters

Learning a Reactive Restart Strategy to Improve Stochastic Search

Solution of the Convergecast Scheduling Problem on a Square Unit Grid When the Transmission Range is 2

An Importance Sampling Approach to the Estimation of Algorithm Performance in Automated Algorithm Design

Lecture Notes in Computer Science - Learning and Intelligent Optimization
Latest Publications