Volume 6 Number 10 (Oct. 2011)
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JSW 2011 Vol.6(10): 2036-2042 ISSN: 1796-217X
doi: 10.4304/jsw.6.10.2036-2042

Multi-objective Optimization of Fuzzy Parallel Machines Scheduling Problem Using Nondominated Genetic Algorithms

Xie Yuan

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.

Index Terms—parallel machines scheduling, fuzzy due-date, NPGA, NSGA-II

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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.

General Information

ISSN: 1796-217X (Online)
Frequency:  Quarterly
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, CNKIGoogle Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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