doi: 10.4304/jsw.6.10.2036-2042
Multi-objective Optimization of Fuzzy Parallel Machines Scheduling Problem Using Nondominated Genetic Algorithms
- Shanghai Dian Ji University/Automation Department, Shanghai, China
Abstract
A kind of unrelated parallel machines scheduling problem is discussed. The memberships of fuzzy due dates denote the grades of satisfaction with respect to completion times with jobs. Objectives of scheduling are to maximize the minimum grade of satisfaction while makespan is minimized in the meantime. Two kind of genetic algorithms are employed to search optimal solution set of the problem. Both Niche Pareto Genetic Algorithm (NPGA) and Nondominated Sorting Genetic Algorithm (NSGA-II) can find the Pareto optimal solutions. Numerical simulation illustrates that NSGA-II has better results than NPGA.
Keywords
- parallel machines scheduling
- fuzzy due-
How to Cite
Xie Yuan, "Multi-objective Optimization of Fuzzy Parallel Machines Scheduling Problem Using Nondominated Genetic Algorithms," Journal of Software, vol. 6, no. 10, pp. 2036-2042, 2011. https://doi.org/ 10.4304/jsw.6.10.2036-2042
Copyright & License
Copyright © 2011 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).