A hybrid development platform for evolutionary multi-objective optimization

Ruimin Shen, Jinhua Zheng, Miqing Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

This paper introduces an optimization template library (OTL), a cross-platform C++ template library for multiobjective optimization. OTL has an object-oriented architecture, which allows that different modules can be arbitrarily combined with each other. Moreover, the C++ template technique is used to increase the flexibility of OTL. Meanwhile, generic programming is widely used in OTL, and the generic algorithms can be used to process different data structures. However, compared with C++, the Python script is more suitable for building the experimental platform. To ensure that all attributes of the experimental results can be fully maintained, a database is used to store the experimental data. Moreover, batch experiments can be easily defined in a set of configuration files; thus, the experiments can be executed automatically without human intervention. In addition, serial and various parallel execution modes are supported, and the user can easily switch the running mode to distributed computing to increase the computing speed. Finally, a highly customizable data visualization tool is created to play back the data sample stored in the database. From a series of comparative studies, the accuracy and running performance of OTL are verified by the statistical results.

Original languageEnglish
Title of host publication2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1885-1892
Number of pages8
ISBN (Electronic)9781479974924
DOIs
Publication statusPublished - 10 Sept 2015
EventIEEE Congress on Evolutionary Computation, CEC 2015 - Sendai, Japan
Duration: 25 May 201528 May 2015

Publication series

Name2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings

Conference

ConferenceIEEE Congress on Evolutionary Computation, CEC 2015
Country/TerritoryJapan
CitySendai
Period25/05/1528/05/15

Bibliographical note

Funding Information:
The authors wish to thank the support of the Hunan Provincial Innovation Foundation For Postgraduate (Grant No. CX2013A011), the National Natural Science Foundation of China (Grant Nos. 61379062, 61372049), the Science Research Project of the Education Office of Hunan Province (Grant Nos. 12A135, 12C0378), the Hunan Province Natural Science Foundation (Grant Nos. 14JJ2072, 13JJ8006), the Science and Technology Project of Hunan Province (Grant No. 2014GK3027), and the Construct Program of the Key Discipline in Hunan Province.

Publisher Copyright:
© 2015 IEEE.

Keywords

  • evolutionary multi-objective optimization
  • generic programming
  • objectoriented architecture

ASJC Scopus subject areas

  • Computer Science Applications
  • Computational Mathematics

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