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Call for Papers Call for Papers

2018 Genetic and Evolutionary Computation Conference (GECCO 2018)

July 15-19, 2018 in Kyoto, Japan
http://iao.hfuu.edu.cn/bbdob-gecco18

 

The Black-Box Discrete Optimization Benchmarking Workshop (BB-DOB@GECCO), a part of the Genetic and Evolutionary Computation Conference (GECCO 2018), is cordially inviting the submission of original and unpublished research papers. Here you can download the BB-DOB@GECCO Workshop Call for Papers (CfP) in PDF format and here as plain text file.

Quantifying and comparing the performance of optimization algorithms is one important aspect of research in search and optimization. The Black-Box-Optimization Benchmarking (BBOB) methodology introduced by the long-standing and successful BBOB-GECCO workshops series has become a well-established standard for benchmarking continuous optimization algorithms. The aim of this workshop is to develop a similar standard methodology for the benchmarking of black-box optimization algorithms for discrete and combinatorial domains. We want to produce:

  1. a well-motivated benchmark function testbed,
  2. a standardized experimental set-up,
  3. rules for measuring and the generation of data output, and
  4. standardized post-processing and presentations for the results in graphs and tables.

All accepted papers in this workshop will be included in the Companion Material Proceedings of the Genetic and Evolutionary Computation Conference 2018 published by ACM and indexed by EI. Authors of selected papers will be invited to submit extended versions of these papers to the Special Issue on Benchmarking of Computational Intelligence Algorithms appearing in the Computational Intelligence journal by Wiley Periodicals Inc., indexed by EI and SCI.

Disclaimer: Two BB-DOB workshops will take place in 2018, i.e., the first edition as BB-DOB@GECCO and the second edition as BB-DOB@PPSN. Both are independent events of the same series.

For more information please contact Pietro S. Oliveto at This email address is being protected from spambots. You need JavaScript enabled to view it..

This workshop is organized as part of the ImAppNIO Cost Action 15140.

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The Black-Box Discrete Optimization Benchmarking Workshop (BB-DOB@PPSN) has just been accepted to be a part of the Fifteenth International Conference on Parallel Problem Solving from Nature (PPSN XV), September 8-12, 2018, in Coimbra, Portugal: http://ppsn2018.dei.uc.pt/).

Quantifying and comparing the performance of optimization algorithms is one important aspect of research in search and optimization. The Black-Box-Optimization Benchmarking (BBOB) methodology introduced by the long-standing and successful BBOB-GECCO workshops series has become a well-established standard for benchmarking continuous optimization algorithms. The aim of workshop is to develop a similar standard methodology for the benchmarking of black-box optimization algorithms for discrete and combinatorial domains. The goal of this second edition of the BB-DOB workshop series is to define a suitable set of benchmark functions for discrete and combinatorial optimization problems.

Our workshop is cordially inviting the submission of original and unpublished research papers. Here you can download the BB-DOB@PPSN Workshop Call for Papers (CfP) in PDF format and here as plain text file. The deadline for workshop submissions will be April 26, 2018.

Disclaimer: Two BB-DOB workshops will take place in 2018, i.e., the first edition as BB-DOB@GECCO and the second edition as BB-DOB@PPSN. Both are independent events of the same series.

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The Black-Box Discrete Optimization Benchmarking Workshop (BB-DOB@GECCO) has just been accepted to be a part of the Genetic and Evolutionary Computation Conference (GECCO 2018), taking place on July 15-19, 2018, in Kyoto, Japan (http://gecco-2018.sigevo.org/).

Quantifying and comparing the performance of optimization algorithms is one important aspect of research in search and optimization. The Black-Box-Optimization Benchmarking (BBOB) methodology introduced by the long-standing and successful BBOB-GECCO workshops series has become a well-established standard for benchmarking continuous optimization algorithms. The aim of this workshop is to develop a similar standard methodology for the benchmarking of black-box optimization algorithms for discrete and combinatorial domains. The goal of this first edition of the BB-DOB workshop series is to define a suitable set of benchmark functions for discrete and combinatorial optimization problems.

Our workshop is cordially inviting the submission of original and unpublished research papers. Here you can download the BB-DOB@GECCO Workshop Call for Papers (CfP) in PDF format and here as plain text file. The deadline for workshop submissions will be April 3, 2018.

Disclaimer: Two BB-DOB workshops will take place in 2018, i.e., the first edition as BB-DOB@GECCO and the second edition as BB-DOB@PPSN. Both are independent events of the same series.

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Today, I had the honor to attend and even speak at a panel of the China (Hefei) Artificial Intelligence International Youth Summit [中国(合肥)人工智能国际青年峰会] organized under the guidance of the Chinese Association for Artificial Intelligence [中国人工智能学会] (CAAI) and the China Computer Federation [中国计算机学会] (CCF) as the delegate of our university [合肥学院]. The conference was a very nice experience and I enjoyed the different talks and discussions at the event. Here I want to shortly summarize some impressions. The summit agenda is preserved here.

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The University Curricula Committee of the IEEE Computational Intelligence Society (IEEE CIS) has created a new subreddit, named /r/CompIntellCourses, in order to build a collection of links to good quality courses on "everything CI." Teachers all over the world are invited to submit their courses, if the teaching material available for free. This is a very nice way to produce an organized catalog of high-quality lectures in the field, making it easier for the everybody to learn about some CI technologies from scratch, or to keep up-to-date with new trends.

Our course Metaheuristic Optimization is one of the first courses that has been included in this list. Metaheuristic optimization is concerned with solving computationally hard problems using soft computing methods and therefore is a field of Computational Intelligence. Our course is based on our previous courses Practical Optimization Algorithm Design taught by Prof. Weise at University of Science and Technology of China (USTC) [中国科学技术大学] and some of the units in the course Evolutionary Computation – Theory and Application which also were taught by Prof. Weise at USTC until 2016. It is, however, significantly extended, improved, and adapted to be an introduction to and overview of the field for both graduate students and research team members in our group at Hefei University [合肥学院].

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