A Combination of PSO and Local Search in University Course Timetabling Problem

被引：7
|
作者：
Irene Sheau Fen Ho [1 ]
Deris Safaai [1 ]
Mohd Hashim, Siti Zaiton [1 ]
机构：
[1] Univ Technol Malaysia, Fac Comp Sc & Info Sys, Johor Darul Tazim, Malaysia
来源：
2009 INTERNATIONAL CONFERENCE ON COMPUTER ENGINEERING AND TECHNOLOGY, VOL II, PROCEEDINGS | 2009年
关键词：
university course timetabling problem; particle swarm optimization; local search; PARTICLE SWARM OPTIMIZATION;
D O I：
10.1109/ICCET.2009.188
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
The university course timetabling problem is a combinatorial optimization problem concerning the scheduling of a number of subjects into a finite number of timeslots in order to satisfy a set of specified constraints. The timetable problem can be very hard to solve, especially when attempting to find a near-optimal solutions, with a large number of instances. This paper presents a combination of particle swarm optimization and local search to effectively search the solution space in solving university course timetabling problem. Three different types of dataset range from small to large are used in validating the algorithm. The experiment results show that the combination of particle swarm optimization and local search is capable to produce feasible timetable with less computational time, comparable to other established algorithms.
引用
收藏
页码：492 / 495
页数：4
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