9783319541563-3319541560-Evolutionary Multi-Criterion Optimization: 9th International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings (Lecture Notes in Computer Science, 10173)

Evolutionary Multi-Criterion Optimization: 9th International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings (Lecture Notes in Computer Science, 10173)

ISBN-13: 9783319541563
ISBN-10: 3319541560
Edition: 1st ed. 2017
Author: Kathrin Klamroth, Yaochu Jin, Oliver Schütze, Günter Rudolph, Heike Trautmann, Margaret Wiecek, Christian Grimme
Publication date: 2017
Publisher: Springer
Format: Paperback 716 pages
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Book details

ISBN-13: 9783319541563
ISBN-10: 3319541560
Edition: 1st ed. 2017
Author: Kathrin Klamroth, Yaochu Jin, Oliver Schütze, Günter Rudolph, Heike Trautmann, Margaret Wiecek, Christian Grimme
Publication date: 2017
Publisher: Springer
Format: Paperback 716 pages

Summary

Evolutionary Multi-Criterion Optimization: 9th International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings (Lecture Notes in Computer Science, 10173) (ISBN-13: 9783319541563 and ISBN-10: 3319541560), written by authors Kathrin Klamroth, Yaochu Jin, Oliver Schütze, Günter Rudolph, Heike Trautmann, Margaret Wiecek, Christian Grimme, was published by Springer in 2017. With an overall rating of 4.1 stars, it's a notable title among other books. You can easily purchase or rent Evolutionary Multi-Criterion Optimization: 9th International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings (Lecture Notes in Computer Science, 10173) (Paperback) from BooksRun, along with many other new and used books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

Description

This book constitutes the refereed proceedings of the 9th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2017 held in Münster, Germany in March 2017.  The 33 revised full papers presented together with 13 poster presentations were carefully reviewed and selected from 72 submissions. The EMO 2017 aims to discuss all aspects of EMO development and deployment, including theoretical foundations; constraint handling techniques; preference handling techniques; handling of continuous, combinatorial or mixed-integer problems; local search techniques; hybrid approaches; stopping criteria; parallel EMO models; performance evaluation; test functions and benchmark problems; algorithm selection approaches; many-objective optimization; large scale optimization; real-world applications; EMO algorithm implementations.
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