Permutation Encoding for Automatic Reconstruction of Connections in Closed-Loop Control System using Evolutionary Algorithm

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Researchers

Research units

  • St. Petersburg National Research University of Information Technologies, Mechanics and Optics (ITMO)
  • Aalto University
  • Luleå University of Technology

Abstract

Search-based software engineering aims to apply different search-based techniques to software engineering problems. Automation of software development is one such problem. In this paper we evaluate the permutation-based individual encoding for automatic reconstruction of measurement connections in a closed-loop control system using evolutionary algorithm and model checking. Using the permutation-based encoding greatly increases the difficulty of the considered problem, but makes it much closer to the real world scenarios. The results show that even the simple (1+1) evolutionary algorithm can successfully solve the realistic optimization problem with large search space size, although it struggles to find the optimal solution within reasonable time on the hardest problem instance.

Details

Original languageEnglish
Title of host publicationProceedings of the 24th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2019
Publication statusPublished - 1 Sep 2019
MoE publication typeA4 Article in a conference publication
EventIEEE International Conference on Emerging Technologies and Factory Automation - Zaragoza, Spain
Duration: 10 Sep 201913 Sep 2019
Conference number: 24

Publication series

NameProceedings IEEE International Conference on Emerging Technologies and Factory Automation
PublisherIEEE
ISSN (Print)1946-0740
ISSN (Electronic)2379-9560

Conference

ConferenceIEEE International Conference on Emerging Technologies and Factory Automation
Abbreviated titleETFA
CountrySpain
CityZaragoza
Period10/09/201913/09/2019

    Research areas

  • Automatic model synthesis, Evolutionary computation, Model checking, Search-based software engineering

ID: 38613338