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Word Processor font optimization in Fixed-function cell Using a Genetic Algorithm

유전자 알고리즘을 이용한 고정 셀에서 글자 폰트(font) 최적화

  • Kim, Sang-Won (Graduate School of Public Policy and Information Technology, Seoul National University of Science and Technology) ;
  • Kim, Seung-Hee (Graduate School of Public Policy and Information Technology, Seoul National University of Science and Technology) ;
  • Kim, Woo-Je (School of Global Convergence of Industrial Engineering, Seoul National University of Science and Technology)
  • 김상원 (서울과학기술대학교 IT정책전문대학원 산업정보시스템전공) ;
  • 김승희 (서울과학기술대학교 IT정책전문대학원 산업정보시스템전공) ;
  • 김우제 (서울과학기술대학교 기술경영융합대학 글로벌융합산업공학과)
  • Received : 2013.07.25
  • Accepted : 2013.08.27
  • Published : 2013.10.31

Abstract

This study was conducted to explore a method of displaying optimized letters that fit the size of tables using a genetic algorithm. As a result, fonts with optimized letters of different lengths were offered through optimum values of the font size, line spacing, and letter spacing by calculating the width and height of the cell and number of letters to be entered. This study is significant in that it provides a solution to letter optimization issues in fixed cells that occur in various word processors that are currently used, through the genetic algorithm.

본 연구는 유전자알고리즘을 사용하여 표의 크기에 맞게 가장 최적화된 글자로 표현할 수 있는 방법을 실험하였다. 그 결과 셀의 넓이와 높이, 입력받을 글자의 개수를 계산하여 글자 크기, 줄 간격, 자간 간격의 최적의 값을 찾아 길이가 서로 다른 글자를 최적화된 상태로 표현할 수 있도록 폰트를 제공할 수 있었다. 본 연구는 유전자 알고리즘을 통하여 현재 사용하고 있는 다양한 워드프로세스에서 발생되고 있는 셀 고정 상태에서의 글자 최적화 문제에 대한 해결 방법을 제시하였다는데 그 의의가 있다.

Keywords

References

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