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

Abstract

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.

Avaliação de um Algoritmo Híbrido na Geração de Soluções para o Problema de Horários de Cursos Universitários

“…e[Gülcü and Akkan 2020] modelaram o CB-CTP como um problema de otimizac ¸ão combinatória multiobjetivo [Akkan and Gülcü 2018]. resolveu o problema com um Multiobjective Genetic Algorithm que faz uso dos algoritmos Hill Climbing e Simulated Annealing e[Gülcü and Akkan 2020] desenvolveram um algoritmo Multi-objective Simulated Annealing [Fajrin and Fatichah 2020]. utilizou um Algoritmo Genético para minimizar a violac ¸ão de restric ¸ões flexíveis do CB-CTP [Song et al 2021].…”

Analisis Performa Dari One-Point, Multi-Point Dan Order Crossover Di Algoritma Genetika

“…Penggunaan GA khususnya pada operator crossover menurut beberapa penelitian sangat penting karena mempengaruhi proses eksplorasi [7] [8] [9]. Penggunaan crossover pada penjadwalan menentukan performa dari proses yang ada di GA [10]. Penelitian terkait penggunaan One-Point dilakukan untuk menyelesaikan optimasi [11] [12].…”