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Optimization and Learning

6th International Conference, OLA 2023, Malaga, Spain, May 3–5, 2023, Proceedings

  • Conference proceedings
  • © 2023

Overview

Editors:
  1. Bernabé Dorronsoro

    1. University of Cadiz, Cadiz, Spain

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  2. Francisco Chicano

    1. University of Malaga, Malaga, Spain

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  3. Gregoire Danoy

    1. University of Luxembourg, Esch-sur-Alzette, Luxembourg

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  4. El-Ghazali Talbi

    1. University of Lille, Lille, France

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Part of the book series: Communications in Computer and Information Science (CCIS, volume 1824)

Included in the following conference series:

Conference proceedings info: OLA 2023.

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Table of contents (32 papers)

  1. Front Matter

    Pages i-xiv
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  2. Advanced Optimization

    1. Front Matter

      Pages 1-1
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    2. A Comparative Study of Fractal-Based Decomposition Optimization

      • T. Firmin, E-G. Talbi
      Pages 3-20

    3. Diagonal Barzilai-Borwein Rules in Stochastic Gradient-Like Methods

      • Giorgia Franchini, Federica Porta, Valeria Ruggiero, Ilaria Trombini, Luca Zanni
      Pages 21-35

    4. Algorithm Selection for Large-Scale Multi-objective Optimization

      • Mustafa Mısır, Xinye Cai
      Pages 36-47

    5. Solving a Multi-objective Job Shop Scheduling Problem with an Automatically Configured Evolutionary Algorithm

      • Jesús Para, Javier Del Ser, Antonio J. Nebro
      Pages 48-61

    6. Solving the Nurse Scheduling Problem Using the Whale Optimization Algorithm

      • Mehdi Sadeghilalimi, Malek Mouhoub, Aymen Ben Said
      Pages 62-73

    7. A Hierarchical Cooperative Coevolutionary Approach to Solve Very Large-Scale Traveling Salesman Problem

      • Rui Zhong, Enzhi Zhang, Masaharu Munetomo
      Pages 74-84

    8. Tornado: An Autonomous Chaotic Algorithm for High Dimensional Global Optimization Problems

      • Nassime Aslimani, El-Ghazali Talbi, Rachid Ellaia
      Pages 85-113

  3. Learning

    1. Front Matter

      Pages 115-115
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    2. Neural Network Information Leakage Through Hidden Learning

      • Arthur Carvalho Walraven da Cunha, Emanuele Natale, Laurent Viennot
      Pages 117-128

    3. Mixing Data Augmentation Methods for Semantic Segmentation

      • Rubén Escobedo, Jónathan Heras
      Pages 129-136

    4. Real-Time Elastic Partial Shape Matching Using a Neural Network-Based Adjoint Method

      • Alban Odot, Guillaume Mestdagh, Yannick Privat, Stéphane Cotin
      Pages 137-147

    5. We Won’t Get Fooled Again: When Performance Metric Malfunction Affects the Landscape of Hyperparameter Optimization Problems

      • Kalifou René Traoré, Andrés Camero, Xiao Xiang Zhu
      Pages 148-160

    6. Condition-Based Maintenance Optimization Under Large Action Space with Deep Reinforcement Learning Method

      • Peng Bi, Yi-Ping Fang, Matthieu Roux, Anne Barros
      Pages 161-172

  4. Learning Methods to Enhance Optimization Tools

    1. Front Matter

      Pages 173-173
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    2. An Application of Machine Learning Tools to Predict the Number of Solutions for a Minimum Cardinality Set Covering Problem

      • Brooks Emerick, Myung Soon Song, Yun Lu, Francis Vasko
      Pages 175-185

    3. Adaptative Local Search for a Pickup and Delivery Problem Applied to Large Parcel Distribution

      • Matthieu Fagot, Laure Brisoux Devendeville, Corinne Lucet
      Pages 186-199

    4. GRAPH Reinforcement Learning for Operator Selection in the ALNS Metaheuristic

      • Syu-Ning Johnn, Victor-Alexandru Darvariu, Julia Handl, Joerg Kalcsics
      Pages 200-212

    5. Multi-objective Optimization of Adhesive Bonding Process in Constrained and Noisy Settings

      • Alejandro Morales-Hernández, Inneke Van Nieuwenhuyse, Sebastian Rojas Gonzalez, Jeroen Jordens, Maarten Witters, Bart Van Doninck
      Pages 213-223
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About this book

This book constitutes the refereed proceedings of the 6th International Conference on Optimization and Learning, OLA 2023, held in Malaga, Spain, during May 3–5, 2023. The 32 full papers included in this book were carefully reviewed and selected from 78 submissions. They were organized in topical sections as follows: advanced optimization; learning; learning methods to enhance optimization tools; optimization applied to learning methods; and real-world applications.



Editors and Affiliations

  • University of Cadiz, Cadiz, Spain

    Bernabé Dorronsoro

  • University of Malaga, Malaga, Spain

    Francisco Chicano

  • University of Luxembourg, Esch-sur-Alzette, Luxembourg

    Gregoire Danoy

  • University of Lille, Lille, France

    El-Ghazali Talbi

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