Title: Group scheduling in a cellular manufacturing shop to minimise total tardiness and nT: a comparative genetic algorithm and mathematical modelling approach

Authors: Gokhan Egilmez; Emre M. Mese; Bulent Erenay; Gürsel A. Süer

Addresses: Department of Industrial and Manufacturing Engineering, North Dakota State University, Fargo, North Dakota ' LeanCor Supply Chain Group, Summerville, South Carolina, USA ' Department of Industrial and Systems Engineering, Ohio University, Athens, OH, USA ' Department of Industrial and Systems Engineering, Ohio University, Athens, OH, USA

Abstract: In this paper, family and job scheduling in a cellular manufacturing shop is addressed where jobs have individual due dates. The objectives are to minimise total tardiness and the number of tardy jobs. Family splitting among cells is allowed but job splitting is not. Two optimisation methods are employed in order to solve this problem, namely mathematical modelling (MM) and genetic algorithm (GA). The results showed that GA found the optimal solution for most of the problems with high frequency. Furthermore, the proposed GA is efficient compared to the MM especially for larger problems in terms of execution times. Other critical aspects of the problem such as family preemption only, impact of family splitting on common due date scenarios and dual objective scenarios are also solved. In short, the proposed comparative approach provides critical insights for the group scheduling problem in a cellular manufacturing shop with distinctive cases.

Keywords: cellular manufacturing systems; CMS; manufacturing cells; total tardiness; operations management; family sequencing; job sequencing; mathematical modelling; genetic algorithms; group scheduling; due dates; family splitting.

DOI: 10.1504/IJSOM.2016.075766

International Journal of Services and Operations Management, 2016 Vol.24 No.1, pp.125 - 146

Received: 09 Sep 2014
Accepted: 11 Oct 2014

Published online: 02 Apr 2016 *

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