Atif Shahzad

Publications (3) View all

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  Article: A procedure to compute a probabilistic bound for the maximum tardiness using stochastic simulation

  Nasser Mebarki, Shahzad Atif
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  ABSTRACT: Dispatching rules are widely used to dynamically schedule the operations in a shop. Their efficiency depends on the performance criteria of interest. One of the most important objectives to deal with in a manufacturing system is the tardiness which can be measured through several performance measures. This paper proposes an effective procedure to estimate the first two central moments (i.e., the mean and the variance) of the conditional tardiness and from this to compute a probabilistic bound for the maximum tardiness. These estimates are computed from the evaluation of the total tardiness, the number of tardy jobs and the root mean square tardiness obtained through a stochastic simulation. Different evaluations done by simulation show the effectiveness of the bound obtained.
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  Article: Correlation Among Tardiness Based Measures for Scheduling using Priority Dispatching Rules

  Nasser Mebarki, Atif Shahzad
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  ABSTRACT: One of the most used methods to schedule manufacturing systems is to use priority dispatching rules (pdrs). It is frequently desired to distinguish the behavior of pdrs in regards with tardiness based performance measures. But, the relation among these performance measures is generally not obvious even for the simple scheduling strategies such as pdrs. In this paper, we first focus on the maximum tardiness that is a very interesting performance measure for the decision-maker in the shop. However, because of its singularity, it is not trivial to assess it. We conducted a simulation study on a benchmark model of a dynamic job-shop system to evaluate the relative performance of a set of pdrs chosen either because these are extensively used or because these exhibit very good performance. Based upon the distribution of the maximum tardiness of these benchmark pdrs, we identify two sub-sets of pdrs. From this, we conducted experiments on the root-mean-square tardiness, which is used to distinguish a system with a few highly tardy jobs from a system with a lot of little tardy jobs. The experiments made show a positive correlation between maximum tardiness and root-mean-square tardiness. Because of the fact that the root-mean-square tardiness is an aggregate measure, it is much more easier to assess it than the maximum tardiness. This provides an opportunity to predict the relative performance of pdrs in regards with the maximum tardiness as well as the width of the tardiness by evaluating root-mean-square tardiness only.
  International Journal of Production Research 01/2012; 00(00):1-14. · 1.12 Impact Factor
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  Article: DISCOVERING DISPATCHING RULES FOR JOB SHOP SCHEDULING PROBLEM THROUGH DATA MINING

  Atif Shahzad, Nasser Mebarki
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  ABSTRACT: A data mining based approach to discover previously unknown priority dispatching rules for job shop scheduling problem is presented. This approach is based upon seeking the knowledge that is assumed to be embedded in the efficient solutions provided by the optimization module built using tabu search. The objective is to discover the scheduling concepts using data mining and hence to obtain a rule-set capable of approximating the efficient solutions in a dynamic job shop scheduling environment. A data mining based scheduling framework is presented.