인타샤(Intarsia) 스웨터 직조를 위한 실 연결 방법의 유전자 알고리즘 해법 연구
A Study on the Genetic Algorithm of Thread’s Connection Method for Intarsia Sweater Weaving
허상무(서울과학기술대학교 IT정책전문대학원); 김우제(서울과학기술대학교)
32권 1호, 35~47쪽
초록
The purpose of this paper is to find an optimal weaving connection method of sweater threads while weaving intarsia sweater by the genetic algorithm. The objective function was devised to minimize labor cost and lessen the amount of thread usage. In order to create the parental population group in the genetic algorithm, we developed five thread connection methods. Besides, elite chromosome screening methods for the offspring group was selected both to the whole chromosome thread elite and to a color-coded elite thread chromosome. Commonly used diamond pattern in Intarsia sweater manufacturing was applied to the experiments. The experimental results showed that thread system saved the labor and material costs than woven method under the existing software. When weaving Intarsia sweater in the field, we can apply the developed genetic algorithm to improve productivity of weaving connection method.
Abstract
The purpose of this paper is to find an optimal weaving connection method of sweater threads while weaving intarsia sweater by the genetic algorithm. The objective function was devised to minimize labor cost and lessen the amount of thread usage. In order to create the parental population group in the genetic algorithm, we developed five thread connection methods. Besides, elite chromosome screening methods for the offspring group was selected both to the whole chromosome thread elite and to a color-coded elite thread chromosome. Commonly used diamond pattern in Intarsia sweater manufacturing was applied to the experiments. The experimental results showed that thread system saved the labor and material costs than woven method under the existing software. When weaving Intarsia sweater in the field, we can apply the developed genetic algorithm to improve productivity of weaving connection method.
- 발행기관:
- 한국경영과학회
- 분류:
- 경영학