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

9783319190839, 9783319190846

Latest Documents Most Cited Documents Contributed Authors Related Sources Related Keywords

Identifying Best Hyperparameters for Deep Architectures Using Random Forests

Lecture Notes in Computer Science - Learning and Intelligent Optimization ◽

10.1007/978-3-319-19084-6_4 ◽

2015 ◽

pp. 29-42 ◽

Cited By ~ 1

Author(s):

Zhen-Zhen Li ◽

Zhuo-Yao Zhong ◽

Lian-Wen Jin

Keyword(s):

Random Forests

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A Practical Case of the Multiobjective Knapsack Problem: Design, Modelling, Tests and Analysis

Lecture Notes in Computer Science - Learning and Intelligent Optimization ◽

10.1007/978-3-319-19084-6_23 ◽

2015 ◽

pp. 249-255

Author(s):

Brahim Chabane ◽

Matthieu Basseur ◽

Jin-Kao Hao

Keyword(s):

Knapsack Problem ◽

Practical Case ◽

Problem Design

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Generating Training Data for Learning Linear Composite Dispatching Rules for Scheduling

Lecture Notes in Computer Science - Learning and Intelligent Optimization ◽

10.1007/978-3-319-19084-6_22 ◽

2015 ◽

pp. 236-248 ◽

Cited By ~ 1

Author(s):

Helga Ingimundardóttir ◽

Thomas Philip Rúnarsson

Keyword(s):

Training Data ◽

Dispatching Rules ◽

Linear Composite ◽

Composite Dispatching Rules

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A Comparative Study on Self-Adaptive Differential Evolution Algorithms for Test Functions and a Real-World Problem

Lecture Notes in Computer Science - Learning and Intelligent Optimization ◽

10.1007/978-3-319-19084-6_12 ◽

2015 ◽

pp. 131-136

Author(s):

Shota Eguchi ◽

Yuki Matsugano ◽

Hirokazu Sakaguchi ◽

Satoshi Ono ◽

Hisato Fukuda ◽

...

Keyword(s):

Comparative Study ◽

Differential Evolution ◽

Real World ◽

Test Functions ◽

Real World Problem ◽

Adaptive Differential Evolution ◽

Evolution Algorithms ◽

Differential Evolution Algorithms ◽

Self Adaptive

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Learning a Hidden Markov Model-Based Hyper-heuristic

Lecture Notes in Computer Science - Learning and Intelligent Optimization ◽

10.1007/978-3-319-19084-6_7 ◽

2015 ◽

pp. 74-88

Author(s):

Willem Van Onsem ◽

Bart Demoen ◽

Patrick De Causmaecker

Keyword(s):

Markov Model ◽

Hidden Markov Model ◽

Hidden Markov ◽

Model Based

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Incremental MaxSAT Reasoning to Reduce Branches in a Branch-and-Bound Algorithm for MaxClique

Lecture Notes in Computer Science - Learning and Intelligent Optimization ◽

10.1007/978-3-319-19084-6_26 ◽

2015 ◽

pp. 268-274 ◽

Cited By ~ 2

Author(s):

Chu-Min Li ◽

Hua Jiang ◽

Ru-Chu Xu

Keyword(s):

Branch And Bound ◽

Branch And Bound Algorithm

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Making EGO and CMA-ES Complementary for Global Optimization

Lecture Notes in Computer Science - Learning and Intelligent Optimization ◽

10.1007/978-3-319-19084-6_29 ◽

2015 ◽

pp. 287-292 ◽

Cited By ~ 4

Author(s):

Hossein Mohammadi ◽

Rodolphe Le Riche ◽

Eric Touboul

Keyword(s):

Global Optimization

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Fitness Landscape of the Factoradic Representation on the Permutation Flowshop Scheduling Problem

Lecture Notes in Computer Science - Learning and Intelligent Optimization ◽

10.1007/978-3-319-19084-6_14 ◽

2015 ◽

pp. 151-164 ◽

Cited By ~ 2

Author(s):

Marie-Eléonore Marmion ◽

Olivier Regnier-Coudert

Keyword(s):

Fitness Landscape ◽

Scheduling Problem ◽

Flowshop Scheduling ◽

Permutation Flowshop ◽

Flowshop Scheduling Problem

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Solving Large MultiZenoTravel Benchmarks with Divide-and-Evolve

Lecture Notes in Computer Science - Learning and Intelligent Optimization ◽

10.1007/978-3-319-19084-6_25 ◽

2015 ◽

pp. 262-267 ◽

Cited By ~ 1

Author(s):

Alexandre Quemy ◽

Marc Schoenauer ◽

Vincent Vidal ◽

Johann Dréo ◽

Pierre Savéant

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Empirical Analysis of Operators for Permutation Based Problems

Lecture Notes in Computer Science - Learning and Intelligent Optimization ◽

10.1007/978-3-319-19084-6_13 ◽

2015 ◽

pp. 137-150

Author(s):

Pierre Desport ◽

Matthieu Basseur ◽

Adrien Goëffon ◽

Frédéric Lardeux ◽

Frédéric Saubion

Keyword(s):

Empirical Analysis

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Lecture Notes in Computer Science - Learning and Intelligent OptimizationLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer International Publishing

Identifying Best Hyperparameters for Deep Architectures Using Random Forests

A Practical Case of the Multiobjective Knapsack Problem: Design, Modelling, Tests and Analysis

Generating Training Data for Learning Linear Composite Dispatching Rules for Scheduling

A Comparative Study on Self-Adaptive Differential Evolution Algorithms for Test Functions and a Real-World Problem

Learning a Hidden Markov Model-Based Hyper-heuristic

Incremental MaxSAT Reasoning to Reduce Branches in a Branch-and-Bound Algorithm for MaxClique

Making EGO and CMA-ES Complementary for Global Optimization

Fitness Landscape of the Factoradic Representation on the Permutation Flowshop Scheduling Problem

Solving Large MultiZenoTravel Benchmarks with Divide-and-Evolve

Empirical Analysis of Operators for Permutation Based Problems

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