지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 발행연도
- 2014.11
- 수록면
- 507 - 517 (11page)
이용수
초록· 키워드
오류제보하기
The university timetabling problem (UTP) has been studied by numerous research groups for decades. The studies were conducted through various methods including linear algorithms, mathematical models, heuristics, and metaheuristics. In this paper, an integer program, a heuristic algorithm, and a hybrid genetic algorithm are used to solve the UTP characterized by real-world constraints such as periodicity and consecutiveness. The integer program can be used to efficiently alter constraints and improve accuracy. However, it is inefficient with large problems, because the UTP is NP-hard problem, so a heuristic algorithm with left upper strategy and a hybrid genetic algorithm were developed. The first experiment showed the effects of the periodicity and consecutiveness constraints ratio and the second experiment compared the performances of the heuristic and hybrid genetic algorithms with small, medium, and large problems. The integer program was coded in FICO Xpress-IVE version 7.3, and the heuristic and the hybrid genetic algorithm were implemented in Java programming language. The results illustrate that the higher ratio of the lectures with consecutiveness constraints deducted the better objectives. For larger problems, the IP could not reach the optimum within 7200 seconds, and the hybrid genetic algorithm yielded better solutions than the heuristic algorithm.
목차
Abstract
1. INTRODUCTION
2. A Mathematical Model
3. Heuristic Algorithm
4. A Hybrid Genetic Algorithm
5. Computational Experiments
6. Conclusions
References
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UCI(KEPA) : I410-ECN-0101-2015-500-002901864