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IIE Transactions
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http://www.tandfonline.com/loi/uiie20An efficient heuristic approach for parallel machine
scheduling with job splitting and sequence-dependent
setup times
a

FAROUK YALAOUI & CHENGBIN CHU

a

a

Laboratory of Industrial Systems Optimization (LOSI), Department of Industrial Systems
Engineering, Troyes University of Technology (UTT), 12, rue Marie Curie, BP 2060, 10010
Troyes, France E-mail: Farouk.Yalaoui@utt.fr orChengbin.Chu@utt.fr
Available online: 29 Oct 2010

To cite this article: FAROUK YALAOUI & CHENGBIN CHU (2003): An efficient heuristic approach for parallel machine scheduling
with job splitting and sequence-dependent setup times, IIE Transactions, 35:2, 183-190
To link to this article: http://dx.doi.org/10.1080/07408170304382

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DOI: 10.1080/07408170390175422

An efficient heuristic approach for parallel machine
scheduling with job splitting and sequence-dependent
setup times
FAROUK YALAOUI* and CHENGBIN CHU
Laboratory of Industrial Systems Optimization (LOSI), Department of Industrial Systems Engineering, Troyes University ofTechnology (UTT), 12, rue Marie Curie, BP 2060, 10010 Troyes, France
E-mail: Farouk.Yalaoui@utt.fr or Chengbin.Chu@utt.fr

Downloaded by [INAOE] at 07:44 16 March 2012

Received January 1999 and accepted January 2002

In this paper, we consider a simplified real-life identical parallel machine scheduling problem with sequence-dependent setup times
and job splitting to minimize makespan. Wepropose a heuristic to solve this problem. Our method is composed of two parts. The
problem is first reduced into a single machine scheduling problem with sequence-dependent setup times. This reduced problem can
be transformed into a Traveling Salesman Problem (TSP), which can be efficiently solved using Little’s method. In the second part,
a feasible initial solution to the original problem isobtained by exploiting the results of the first part. This initial solution is then
improved in a step by step manner, taking into account the setup times and job splitting. We develop a lower bound and evaluate
the performances of our heuristic on a large number of randomly generated instances. The solution given by our heuristic is less
than 4.88% from the lower bound.

1. Introduction
Theproblem addressed in this work is an identical parallel machine scheduling problem in which it is necessary
to change setups between the processing of different
parts. The setup times are sequence-dependent. Each job
can be split into sections, which can be processed in
parallel on different machines. The difference between job
splitting and preemption is that with job splitting the
different...
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