A New Biological Operator in Genetic Algorithm for Class Scheduling Problem
A New Biological Operator in Genetic Algorithm for Class Scheduling Problem
复制标题
DOI：
10.5120/9742-4293
复制
发表时间：
2012-12
期刊：
影响因子：
--
通讯作者：
Lakshmi K. Vivekanandhan;R. Brintha;Sanjay R. Sutar;R. Bichkar;Leon Bambrick;Mila S. de Magalh ̃aes
中科院分区：
文献类型：
--
作者：
Lakshmi K. Vivekanandhan;R. Brintha;Sanjay R. Sutar;R. Bichkar;Leon Bambrick;Mila S. de Magalh ̃aes
本文描述了一种新的方法来解决班级调度问题，这是一个约束组合NP难问题。从自然进化的奇迹中，RNA干扰诱导沉默复合体(RISC)这一重要现象可以作为干扰诱导沉默算子，并将其融入到遗传算法中来解决任何实际问题，如排课问题。本研究的目的是通过一种新的生物启发算子--干扰诱导沉默(IIS)算子，建立一个利用遗传算法解决排课问题的自动化系统，该算子可以用来设置即时的特定偏好，并利用交叉和变异等概率算子来生成有效的时间表。适应度函数的框架考虑了硬约束和软约束。实验结果表明，该算法比简单遗传算法更有效。
paper describes an innovative approach to solve Class Scheduling problem which is a constraint combinatorial NP hard problem. From the wonders of natural evolution, an important phenomenon of RNA interference induced silencing complex (RISC) can be used as Interference Induced Silencing operator and it is incorporated into the Genetic Algorithm to solve any practical problems like Class Scheduling problem. The aim of this research is to create an automated system for class scheduling problem using Genetic Algorithm to the extent by a new biologically inspired operator, Interference Induced Silencing (IIS) operator that it can be used to set the instant specific preferences to generate the effective time table with the probabilistic operators like crossover and mutation. The framework of the fitness function has considered the hard constraints and the soft constraints. The results were proved to be efficient than the simple Genetic algorithm.