Recent Advances in Evolutionary Multi-objective Optimization

  • Slim Bechikh
  • Rituparna Datta
  • Abhishek Gupta

Part of the Adaptation, Learning, and Optimization book series (ALO, volume 20)

Table of contents

  1. Front Matter
    Pages i-xii
  2. Maha Elarbi, Slim Bechikh, Lamjed Ben Said, Rituparna Datta
    Pages 1-30
  3. Radhia Azzouz, Slim Bechikh, Lamjed Ben Said
    Pages 31-70
  4. Ankur Sinha, Pekka Malo, Kalyanmoy Deb
    Pages 71-103
  5. Slim Bechikh, Maha Elarbi, Lamjed Ben Said
    Pages 105-137
  6. Abhishek Gupta, Bingshui Da, Yuan Yuan, Yew-Soon Ong
    Pages 139-157
  7. Arun Kumar Sharma, Rituparna Datta, Maha Elarbi, Bishakh Bhattacharya, Slim Bechikh
    Pages 159-179

About this book

Introduction

This book covers the most recent advances in the field of evolutionary multiobjective

optimization. With the aim of drawing the attention of up-andcoming

scientists towards exciting prospects at the forefront of computational

intelligence, the authors have made an effort to ensure that the ideas conveyed

herein are accessible to the widest audience. The book begins with a summary

of the basic concepts in multi-objective optimization. This is followed by brief

discussions on various algorithms that have been proposed over the years for

solving such problems, ranging from classical (mathematical) approaches to

sophisticated evolutionary ones that are capable of seamlessly tackling practical

challenges such as non-convexity, multi-modality, the presence of multiple

constraints, etc. Thereafter, some of the key emerging aspects that are likely

to shape future research directions in the field are presented. These include:<

optimization in dynamic environments, multi-objective bilevel programming,

handling high dimensionality under many objectives, and evolutionary multitasking.

In addition to theory and methodology, this book describes several

real-world applications from various domains, which will expose the readers

to the versatility of evolutionary multi-objective optimization.

Keywords

Computational Intelligence Multi-Objective Optimization Evolutionary Computation Decision Making Dynamic Optimization Constrained Optimization Bi-Level Programming Multi-Tasking Applications

Editors and affiliations

  • Slim Bechikh
    • 1
  • Rituparna Datta
    • 2
  • Abhishek Gupta
    • 3
  1. 1.SOIE lab, Computer Science DepartmentUniversity of Tunis, ISG-Tunis Bouchoucha, Le BardoTunisia
  2. 2.Department of Mechanical EngineeringInstitute of Technology, KalyanpurKanpurIndia
  3. 3.School of Computer EngineeringNanyang Technological UniversitySingaporeSingapore

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-42978-6
  • Copyright Information Springer International Publishing Switzerland 2017
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-319-42977-9
  • Online ISBN 978-3-319-42978-6
  • Series Print ISSN 1867-4534
  • Series Online ISSN 1867-4542
  • About this book