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
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;
Conference_Titel :
Information Technology: New Generations (ITNG), 2010 Seventh International Conference on
Conference_Location :
Las Vegas, NV
Print_ISBN :
978-1-4244-6270-4
DOI :
10.1109/ITNG.2010.184