Adaptive PBIL algorithm and its application to solve scheduling problems

被引：0
|
作者：
Pang, Hali [1 ]
Hu, Kunyuan
Hong, Zongyou
机构：
[1] Nat Sci Fdn, Liaoning, Peoples R China
[2] NE Univ, Coll Informat Sci & Engn, Shenyang 110004, Peoples R China
[3] Chinese Acad Sci, Shenyang Inst Automat, Shenyang 110004, Peoples R China
来源：
2006 IEEE CONFERENCE ON COMPUTER-AIDED CONTROL SYSTEM DESIGN, VOLS 1 AND 2 | 2006年
关键词：
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：
An adaptive population-based incremental learning algorithm (APBIL) is presented basing on analyzing the characteristics of traditional PBIL algorithm in this paper. Overcoming disadvantages of traditional PBIL algorithm, the proposed APBIL algorithm can adjust learning rate and mutation probability automatically according to the evolution degree of the algorithm's searching performed. Extensive computational tests with Flow shop and Job shop scheduflng problems are carried out. The results compared with standard PBIL algorithm's and genetic algorithm's show that the proposed algorithm exceed the traditional PBIL algorithm and GA in calculation efficiency and search capability. The proposed algorithm can acquire stable high quality solution.
引用
收藏
页码：181 / 186
页数：6
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