Comparing genetic operators for the timetabling problem

Hideg, Attila

doi:10.1109/sami.2015.7061845

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2020

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“…The fitness function is used as a parameter to candidates irrespective of the problem [19]. It also depends on the specifications of the problem that needs to be solved.…”

Section: Fitness Functionmentioning

confidence: 99%

Multi-parent order crossover mechanism of genetic algorithm for minimizing violation of soft constraint on course timetabling problem

Fajrin

Fatichah

2020

register. jurnal. ilm. teknologi. sistem. inf.

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A crossover operator is one of the critical procedures in genetic algorithms. It creates a new chromosome from the mating result to an extensive search space. In the course timetabling problem, the quality of the solution is evaluated based on the hard and soft constraints. The hard constraints need to be satisfied without violation while the soft constraints allow violation. In this research, a multi-parent crossover mechanism is used to modify the classical crossover and minimize the violation of soft constraints, in order to produce the right solution. Multi-parent order crossover mechanism tends to produce better chromosome and also prevent the genetic algorithm from being trapped in a local optimum. The experiment with 21 datasets shows that the multi-parent order crossover mechanism provides a better performance and fitness value than the classical with a zero fitness value or no violation occurred. It is noteworthy that the proposed method is effective to produce available course timetabling.

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“…The fitness function is used as a parameter to candidates irrespective of the problem [19]. It also depends on the specifications of the problem that needs to be solved.…”

Section: Fitness Functionmentioning

confidence: 99%

Multi-parent order crossover mechanism of genetic algorithm for minimizing violation of soft constraint on course timetabling problem

Fajrin

Fatichah

2020

register. jurnal. ilm. teknologi. sistem. inf.

View full text Add to dashboard Cite

show abstract

Comparing genetic operators for the timetabling problem

Cited by 1 publication

References 12 publications

Multi-parent order crossover mechanism of genetic algorithm for minimizing violation of soft constraint on course timetabling problem

Multi-parent order crossover mechanism of genetic algorithm for minimizing violation of soft constraint on course timetabling problem

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