
doi: 10.2139/ssrn.1863757
Genetic Algorithm (GA) is one of the most popular optimization solutions. It has been implemented in various applications such as scheduling. Badly designed timetables are not just inconvenient but proved expensive in terms of wasting time and money. The flows of GA are using selection, crossover and mutation operators applied to populations of chromosomes. This paper proposes the powerful techniques using GA in scheduling. School timetabling problem is one of the applications in scheduling. In one aspect, it deals with class and Teachers such that it fulfils the process time slot. These aspects are important for the School timetabling so it can be done in a smooth way and no teacher can sit more than one subject in a same time slot. The other constraint is the teacher workload should be arranged less than three subject in a row.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
