Multiobjective Scheduling by Multiobjective Evolutionary Algorithm and Shifting Bottleneck Procedure
Date Issued
2009
Date
2009
Author(s)
Cheng, Hsueh-Chien
Abstract
In this thesis, a multiobjective scheduling problem is addressed. Since cycle time-based objectives and due date-based objectives frequently contradicts with each other, a well-balanced schedule is important for manufacturing systems. A two-stage algorithm, multiobjective memetic algorithm and shifting bottleneck, MOMASB, is proposed to solve multiobjective scheduling problem. The first stage is a memetic algorithm, RMA, to generate initial schedules followed by the second stage, which is a re-optimization procedure inspired by SB. The components of the proposed RMA are carefully designed to maintain a balance between exploration and exploitation. In the second stage, the re-optimization applys a memetic algorithm-based subproblem, SSPMA. Experimental results compared with a recent approach in the literature show the effectiveness of the proposed MOMASB. The promising results indicate the potential of MOMASB to be applied to practical use.
Subjects
Production scheduling
Multiobjective optimization
Evolutionary algorithm
Shifting bottleneck
Type
thesis
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