Title: Comparative studies on design of experiments for tuning parameters in a genetic algorithm for a scheduling problem

Authors: Arif Arin, Ghaith Rabadi, Resit Unal

Addresses: Engineering Management and Systems Engineering Department, Frank Batten College of Engineering and Technology, Old Dominion University, Norfolk, Virginia 23529, USA. ' Engineering Management and Systems Engineering Department, Frank Batten College of Engineering and Technology, Old Dominion University, Norfolk, Virginia 23529, USA. ' Engineering Management and Systems Engineering Department, Frank Batten College of Engineering and Technology, Old Dominion University, Norfolk, Virginia 23529, USA

Abstract: Metaheuristic algorithms have shown to work well with large scale optimisation problems as they obtain optimal or near-optimal solutions. However, most metaheuristics have several parameters that need to be tuned before they can reach good results. Design of experiments (DoE) methods offer practical approaches to tune the parameters effectively. In this paper, we seek the best parameter setting for a genetic algorithm (GA) that is developed to solve the single machine total weighted tardiness problem. To tune the GA parameters, multiple DOE methods are employed and their results are compared. According to their fitness performances in both single and multiple runs, D-optimal and S/N ratio designs found the best parameter settings among DOE methods presented. Additionally, S/N ratio design showed quite robust results for different problem sizes.

Keywords: design of experiments; DOE; full factorial design, orthogonal arrays; central composite design; CCD; D-optimal design; signal-to-noise ratio; S/N ratio; parameter tuning; total tardiness; genetic algorithms; single machine total weighted tardiness; scheduling.

DOI: 10.1504/IJEDPO.2011.040262

International Journal of Experimental Design and Process Optimisation, 2011 Vol.2 No.2, pp.102 - 124

Published online: 11 Oct 2014 *

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