Abstract
Timetabling Problem (TP) was analyzed detailedly, an optimization mathematical model of TP was established, and the framework structure to solving TP was found. According to characteristics of TP, GA was introduced, a variety of improved schemes were designed , includes: decimal code scheme, initial population design scheme ,fitness function design scheme, the best chromosome replacing strategy, adaptive crossover probability and adaptive mutation probability design scheme. Simulation results show that the proposed GA can satisfy multiple constraint conditions and resolve Timetabling Problem more effectively.
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