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Showing 5 results for Niaki

Seyed Taghi Akhavan Niaki, Mohammad Saber Fallah Nezhad,
Volume 1, Issue 2 (6-2009)

Fallahnezhad, Niaki,
Volume 2, Issue 2 (6-2011)

  A novel optimal single machine replacement policy using a single as well as a two-stage decision making process is proposed based on the quality of items produced. In a stage of this policy, if the number of defective items in a sample of produced items is more than an upper threshold, the machine is replaced. However, the machine is not replaced if the number of defective items is less than a lower threshold. Nonetheless, when the number of defective item falls between the upper and the lower thresholds, the decision making process continues inspecting and possibly repairing the machine and the decision making process goes on to collect more samples. The primary objective of own work is to determine the optimal values of both the upper and the lower thresholds using a Markov process to minimize the total cost associated with a machine replacement policy.

Akhavan Niaki, Fallah Nezhad,
Volume 3, Issue 1 (4-2012)

We develop an optimization model based on Markovian approach to determine the optimum value of thresholds in a proposed acceptance sampling design. Consider an acceptance sampling plan where items are inspected and when the number of conforming items between successive defective items falls below a lower control threshold value, then the batch is rejected, and if it falls above a control threshold value, then the batch is accepted and if it falls within the thresholds, the process of inspecting the items continues. A decision is made to accept or reject the batch. We begin with developing a Markov model for determining performance measures of sampling designs, resulting in an acceptance sampling plan optimized based on the minimum angle method. Then, the performance measures of the acceptance sampling plan are determined and the optimum values of thresholds are selected in order to optimize the objective functions. In order to demonstrate the application of the proposed methodology, numerical examples are illustrated.
M.s. Fallah Nezhad, S.t.a. Niaki, E. Shahin,
Volume 4, Issue 2 (10-2013)

Our aim is to maximize expected profit per item of a multi-stage production system by determining best adjustment points of the equipments used based on technical product specifications defined by designer. In this system, the quality characteristics of items produced should be within lower and higher tolerance limits. When a quality characteristic of an item either falls beneath the lower limit or lies above the upper limit, it is reworked or classified as scrap, each with its own cost. A function of the expected profit per item is first presented based on equipment adjustment points. Then, the problem is modeled by a Markovian approach. Finally, numerical examples are solved in order to illustrate the proposed model.
Mr. Mehdi Keramatpour, Prof. Seyed Taghi Akhavan Niaki, Dr. Seyed Hamid Reza Pasandideh,
Volume 9, Issue 2 (6-2018)

In this paper, a novel scenario-based two-level inventory control model with a limited budget is formulated. The demand during the selling period is considered to follow a uniform probability distribution. In addition, it is assumed that there will be some customers who are willing to wait for their demands to be satisfied; thus a service level is considered for these customers. The aim is to find the optimal order quantities of the products and the required raw materials such that the relevant expected total profit obtained during the period is maximized. After proving the convexity of the proposed formulation, a penalty function and the Barrier method is proposed to solve the developed nonlinear stochastic programming problem. The problem is solved under different demand scenarios defined in three states of good, fair, and low. Finally, a case study in a dairy manufacturing company is provided to illustrate the application of the proposed methodology in real-world inventory control systems.  

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مجله انجمن ایرانی تحقیق در عملیات Iranian Journal of Operations Research
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