In this application of artificial intelligence to a real-world problem, the constrained scheduling of employee resourcing for a mall type shop is solved by means of a genetic algorithm. hromosomes encode a one-week schedule and a constraint matrix handles all requirements for the population. The genetic operators are purposely designed to preserve all constraints and the objective function assures an imposed coverage, this is for people on both sections of the mall. The results demonstrate that the genetic algorithm approach can provide acceptable solutions to this type of employee scheduling problem with constrains.
목차
Abstract 1. Introduction 2. Problem formulation 3. Problem solution 3.1. Chromosome encoding 3.2. Objective function 3.3. Constraint setting 3.4. Initial population 3.5. Mutation operator 3.6. Cross-over operator 3.7. Elitism 3.8. Other genetic algorithm settings 4. Results 5. Conclusion References
키워드
Genetic AlgorithmsScheduling Problem.
저자
Adrian Brezulianu [ Faculty of Electronics, Telecommunications and Information Technology, Technical University of Iasi ]
Monica Fira [ Institute of Computer Science, Romanian Academy, Iasi Branch ]
Lucian Fira [ Faculty of Electronics, Telecommunications and Information Technology, Technical University of Iasi ]
보안공학연구지원센터(IJAST) [Science & Engineering Research Support Center, Republic of Korea(IJAST)]
설립연도
2006
분야
공학>컴퓨터학
소개
1. 보안공학에 대한 각종 조사 및 연구
2. 보안공학에 대한 응용기술 연구 및 발표
3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최
4. 보안공학 기술의 상호 협조 및 정보교환
5. 보안공학에 관한 표준화 사업 및 규격의 제정
6. 보안공학에 관한 산학연 협동의 증진
7. 국제적 학술 교류 및 기술 협력
8. 보안공학에 관한 논문지 발간
9. 기타 본 회 목적 달성에 필요한 사업
간행물
간행물명
International Journal of Advanced Science and Technology
간기
월간
pISSN
2005-4238
수록기간
2008~2016
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of Advanced Science and Technology vol.14