DocumentCode
2896176
Title
Three Genetic Algorithm Approaches to Parallel Machine Scheduling and Comparison with a Heuristic
Author
Samur, Sumeyye ; Bulkan, Serol
Author_Institution
Dept. of Ind. Eng., Marmara Univ., Istanbul, Turkey
fYear
2010
fDate
12-14 April 2010
Firstpage
270
Lastpage
274
Abstract
In this research, we aim to assign jobs, having different processing and release times, to identical parallel machines in the most effective way. To do so; firstly we made a literature review to see what other researchers have done in this area. Secondly, we proposed three genetic algorithms each having different crossover methods. And at the end; we examined those three algorithms and also a heuristic which we already proposed and tested before. Based on the job size and machine size, some algorithms performed better results than others.
Keywords
computational complexity; genetic algorithms; scheduling; crossover methods; genetic algorithm; heuristic comparison; parallel machine scheduling; Genetic algorithms; Heuristic algorithms; Industrial engineering; Information technology; Job shop scheduling; Parallel machines; Polynomials; Scheduling algorithm; Testing; Time factors; genetic algorithm; heuristic; makespan; parallel machine scheduling; release time;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Technology: New Generations (ITNG), 2010 Seventh International Conference on
Conference_Location
Las Vegas, NV
Print_ISBN
978-1-4244-6270-4
Type
conf
DOI
10.1109/ITNG.2010.184
Filename
5501719
Link To Document