Improving an evolutionary approach to Sudoku Puzzles by intermediate optimization of the population

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Autoren

  • Matthias Becker
  • Sinan Balci
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Details

OriginalspracheEnglisch
Titel des SammelwerksInformation Science and Applications 2018
UntertitelICISA 2018
Herausgeber/-innenKuinam J. Kim, Nakhoon Baek
Herausgeber (Verlag)Springer Singapore
Seiten369-375
Seitenumfang7
Auflage1.
ISBN (elektronisch)978-981-13-1056-0
ISBN (Print)978-981-13-4557-9, 978-981-13-1055-3
PublikationsstatusVeröffentlicht - 24 Juli 2019
VeranstaltungInternational Conference on Information Science and Applications, ICISA 2018 - Kowloon, Hongkong
Dauer: 25 Juni 201827 Juni 2018

Publikationsreihe

NameLecture Notes in Electrical Engineering
Band514
ISSN (Print)1876-1100
ISSN (elektronisch)1876-1119

Abstract

In this work we improve previous approaches based on genetic algorithms (GA) to solve sudoku puzzles. Those approaches use random swap mutations and filtered mutations, where both operations result in relatively slow convergence, the latter suffering a bit less. We suggest to improve GA based approaches by an intermediate local optimization step of the population. Compared to the previous approaches our approach is superior in terms of convergence rate, success rate and speed. As consequence we find the optimum with one population member and within one generation in a few milliseconds instead of nearly one minute.

ASJC Scopus Sachgebiete

Zitieren

Improving an evolutionary approach to Sudoku Puzzles by intermediate optimization of the population. / Becker, Matthias; Balci, Sinan.
Information Science and Applications 2018: ICISA 2018. Hrsg. / Kuinam J. Kim; Nakhoon Baek. 1. Aufl. Springer Singapore, 2019. S. 369-375 (Lecture Notes in Electrical Engineering; Band 514).

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Becker, M & Balci, S 2019, Improving an evolutionary approach to Sudoku Puzzles by intermediate optimization of the population. in KJ Kim & N Baek (Hrsg.), Information Science and Applications 2018: ICISA 2018. 1. Aufl., Lecture Notes in Electrical Engineering, Bd. 514, Springer Singapore, S. 369-375, International Conference on Information Science and Applications, ICISA 2018, Kowloon, Hongkong, 25 Juni 2018. https://doi.org/10.1007/978-981-13-1056-0_38
Becker, M., & Balci, S. (2019). Improving an evolutionary approach to Sudoku Puzzles by intermediate optimization of the population. In K. J. Kim, & N. Baek (Hrsg.), Information Science and Applications 2018: ICISA 2018 (1. Aufl., S. 369-375). (Lecture Notes in Electrical Engineering; Band 514). Springer Singapore. https://doi.org/10.1007/978-981-13-1056-0_38
Becker M, Balci S. Improving an evolutionary approach to Sudoku Puzzles by intermediate optimization of the population. in Kim KJ, Baek N, Hrsg., Information Science and Applications 2018: ICISA 2018. 1. Aufl. Springer Singapore. 2019. S. 369-375. (Lecture Notes in Electrical Engineering). doi: 10.1007/978-981-13-1056-0_38
Becker, Matthias ; Balci, Sinan. / Improving an evolutionary approach to Sudoku Puzzles by intermediate optimization of the population. Information Science and Applications 2018: ICISA 2018. Hrsg. / Kuinam J. Kim ; Nakhoon Baek. 1. Aufl. Springer Singapore, 2019. S. 369-375 (Lecture Notes in Electrical Engineering).
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