Curriculum Schedule Arrangement Solved by an Improved Immune Optimization Algorithm

Xiao Feng Li; An  Shi; Jian Guo  Luo

doi:10.4028/www.scientific.net/AMR.756-759.3556

Paper Titles

Study on the Multi-Core DSP Parallel Processing of Polarization Images Registration
p.3532

A New Conjugate Gradient Projection Method and its Application
p.3537

An Effective Image Fusion Method Based on Nonsubsampled Contourlet Transform and Pulse Coupled Neural Network
p.3542

Gene Prediction Based on One-Dimensional Image Segmentation
p.3549

Curriculum Schedule Arrangement Solved by an Improved Immune Optimization Algorithm
p.3556

A Localization Algorithm of Multi-Hop Three Dimensional AOA with Space-Based Angle Transmission and its Application
p.3562

Research on Node Localization Algorithm in WSN Basing Machine Learning
p.3568

Synchronous Optimization Method for Heterogeneous Database Based on the Minimal Data Set
p.3574

Blind Image Separation Based on an Optimized Fast Fixed Point Algorithm
p.3578

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 756-759Curriculum Schedule Arrangement Solved by an...

Curriculum Schedule Arrangement Solved by an Improved Immune Optimization Algorithm

Abstract:

To solve the university timetabling problem (UTP) effectively, a immune algorithm-based solution for UTP was proposed. The mathematical model of UTP was expounded, a framework of immune algorithm was given, and simulation experiments were done to validate algorithm. Experimental result shows that proposed algorithm can solve the UTP effectively, and has the advantage of good application value.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 756-759)

Pages:

3556-3561

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.756-759.3556

Citation:

Cite this paper

Online since:

September 2013

Authors:

Xiao Feng Li, An Shi, Jian Guo Luo

Keywords:

Component, Immune Optimization Algorithm, Matrix Coding, University Timetabling Problem

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Tan yong, wang ling. Course timetabling system based on genetic algorithm. computer application, PP. 108-111, (2002).

Google Scholar

[2] Tengzi, Denghuiwen. Based on the genetic algorithm in the course scheduling system design and Implementation. computer application, PP. 199-203, (2007).

Google Scholar

[3] Pengfuming, wuzhijian. Based on multi-population genetic algorithm in course scheduling method . Computer engineering and design, PP. 4877-4881, (2010).

Google Scholar

[4] Zhanghuawei, yangkai, Particle swarm optimization algorithm based on the research of course scheduling . Journal of Zhengzhou University of Light Industry, PP. 49-52, (2010).

Google Scholar

[5] Wu xia, Jiangyuming. The use of immune particle swarm optimization algorithm to solve scheduling problem. Computer engineering and design, PP. 4877-4881, (2010).

Google Scholar

[6] N. Pillay, W. Banzhaf．An informed genetic algorithm for the examination timetabling problem. Applied Soft Computing, PP. 457-467, (2011).

DOI: 10.1016/j.asoc.2009.08.011

Google Scholar