title: Hybrid metaheuristics for solving a fuzzy single batch-processing machine scheduling problem.
abstract: 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.
authors.affiliation: Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.
authors.forename: S
authors.initials: S
authors.lastname: Molla-Alizadeh-Zavardehi
authors.affiliation: School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran.
authors.forename: R
authors.initials: R
authors.lastname: Tavakkoli-Moghaddam
authors.affiliation: Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran.
authors.forename: F Hosseinzadeh
authors.initials: FH
authors.lastname: Lotfi
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D017143:Fuzzy Logic; D008962:Models, Theoretical; D010561:Personnel Staffing and Scheduling; D011382:Programming, Linear