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The Scientific World Journal
Volume 2014, Article ID 214615, 10 pages
Research Article

Hybrid Metaheuristics for Solving a Fuzzy Single Batch-Processing Machine Scheduling Problem

1Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
2School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran
3Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran

Received 14 February 2014; Accepted 30 March 2014; Published 22 April 2014

Academic Editors: P. Agarwal, V. Bhatnagar, and Y. Zhang

Copyright © 2014 S. Molla-Alizadeh-Zavardehi et al. 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.


This paper deals with a problem of minimizing total weighted tardiness of jobs in a real-world single batch-processing machine (SBPM) scheduling in the presence of fuzzy due date. In this paper, first a fuzzy mixed integer linear programming model is developed. Then, due to the complexity of the problem, which is NP-hard, we design two hybrid metaheuristics called GA-VNS and VNS-SA applying the advantages of genetic algorithm (GA), variable neighborhood search (VNS), and simulated annealing (SA) frameworks. Besides, we propose three fuzzy earliest due date heuristics to solve the given problem. Through computational experiments with several random test problems, a robust calibration is applied on the parameters. Finally, computational results on different-scale test problems are presented to compare the proposed algorithms.