Research on Solving Timetabling Problem Based on Improved Retrospective Algorithm

被引：0
|
作者：
Song, Jie [1 ]
机构：
[1] Kunming Univ, Sch Informat Technol, Kunming, Peoples R China
来源：
PROCEEDINGS OF THE 2016 4TH INTERNATIONAL CONFERENCE ON MACHINERY, MATERIALS AND COMPUTING TECHNOLOGY | 2016年 / 60卷
关键词：
Timetabling; Retrospective algorithm; Fitness function; Hard constraint; Soft constraint;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The algorithms for timetabling have been widely studied but there are no perfect solutions for it yet. Through investigating and comparing the existing algorithms, it has been found that these algorithms can be classified into two categories designated as constructed algorithms and modern algorithms, which show the individual advantages and shortages. In this improved algorithm, the genetic algorithm and some useful rules have been introduced into the retrospective algorithm. The practical application proves that the improved retrospective algorithm is especially suitable as a timetabling system.
引用
收藏
页码：104 / 109
页数：6
相关论文
共 50 条
  • [1] Solving a timetabling problem with an artificial bee colony algorithm
    Chen, Tinggui
    Xu, Chonghuan
    [J]. World Transactions on Engineering and Technology Education, 2015, 13 (03): : 438 - 442
  • [2] Solving the course timetabling problem with a hybrid heuristic algorithm
    Lue, Zhipeng
    Hao, Jin-Kao
    [J]. ARTIFICIAL INTELLIGENCE: METHODOLOGY, SYSTEMS, AND APPLICATIONS, 2008, 5253 : 262 - 273
  • [3] Solving a School Timetabling Problem Using a Bee Algorithm
    Lara, Carlos
    Flores, Juan J.
    Calderon, Felix
    [J]. MICAI 2008: ADVANCES IN ARTIFICIAL INTELLIGENCE, PROCEEDINGS, 2008, 5317 : 664 - 674
  • [4] A Utilization-based Genetic Algorithm for Solving the University Timetabling Problem (UGA)
    Abdelhalim, Esraa A.
    El Khayat, Ghada A.
    [J]. ALEXANDRIA ENGINEERING JOURNAL, 2016, 55 (02) : 1395 - 1409
  • [5] Optimize Timetabling Problem Using Improved Genetic Algorithm
    Yun, Wang Xiao
    Kun, Wang Feng
    Wang XiangYun
    [J]. 2008 IEEE INTERNATIONAL SYMPOSIUM ON KNOWLEDGE ACQUISITION AND MODELING WORKSHOP PROCEEDINGS, VOLS 1 AND 2, 2008, : 260 - +
  • [6] Novel operators for quantum evolutionary algorithm in solving timetabling problem
    Tayarani-N., Mohammad-H.
    [J]. EVOLUTIONARY INTELLIGENCE, 2021, 14 (04) : 1869 - 1893
  • [7] Genetic algorithm solving a weekly course-timetabling problem
    Erben, W.
    Keppler, J.
    [J]. Lecture Notes in Computer Science, 1153
  • [8] Novel operators for quantum evolutionary algorithm in solving timetabling problem
    Mohammad-H. Tayarani-N.
    [J]. Evolutionary Intelligence, 2021, 14 : 1869 - 1893
  • [9] Developing inverted simulated annealing algorithm and solving timetabling problem
    Kim, M
    Lee, S
    Chung, T
    [J]. INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOL I AND II, 1999, : 634 - 639
  • [10] A self-adapting genetic algorithm for solving the university timetabling problem
    Perzina, R
    [J]. 8TH WORLD MULTI-CONFERENCE ON SYSTEMICS, CYBERNETICS AND INFORMATICS, VOL V, PROCEEDINGS: COMPUTER SCIENCE AND ENGINEERING, 2004, : 284 - 288
12345