DocumentCode
694314
Title
An improved chaos immune algorithm based on Hadoop framework to solve job-shop scheduling problem
Author
Xu Liang ; Minyi Wang ; Xuan Jiao ; Ming Huang
Author_Institution
Software Technol. Inst., Dalian Jiaotong Univ., Dalian, China
fYear
2013
fDate
12-13 Oct. 2013
Firstpage
5
Lastpage
9
Abstract
Based on the analysis of the inadequate of chaos immune algorithm, an improved chaos immune algorithm for solving job-shop problem is presented. Use combined chaos mapping to increase the diversity of the initial population and Map-Reduce method to reduce the time complexity of algorithm based on Hadoop framework. Through the experiment of antibody population initialization and classic JSSP benchmark, the increase of the performance and effect of the algorithm is verified.
Keywords
chaos; computational complexity; job shop scheduling; parallel processing; Hadoop framework; JSSP benchmark; Map-Reduce method; chaos mapping; improved chaos immune algorithm; job-shop scheduling problem; time complexity; Algorithm design and analysis; Arrays; Job shop scheduling; Sociology; Statistics; Time complexity; Chaos Immune Algorithm; Combined Chaos Mapping; Hadoop framework; Job Shop Scheduling Problem;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Network Technology (ICCSNT), 2013 3rd International Conference on
Conference_Location
Dalian
Type
conf
DOI
10.1109/ICCSNT.2013.6967052
Filename
6967052
Link To Document