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Articles by Seyed Taghi Akhavan Niaki
Total Records ( 3 ) for Seyed Taghi Akhavan Niaki
  Ata Allah Taleizadeh , Seyed Taghi Akhavan Niaki and Mir-Bahador Aryanezhad
  While in multi-periodic inventory control problems the usual assumption are that the orders are placed at the beginning of each period (periodic review) or depending on the inventory level they can happen at any time (continuous review), in this research, we relax these assumptions and assume that the periods between two replenishments of the products are independent and identically distributed random variables. Furthermore, assuming the purchasing price are triangular fuzzy variables, the quantities of the orders are of integer-type and that there are space, budget and service level constraints, incremental discount is considered to purchase products and a combination of back-order and lost-sales are taken into account for the shortages. We show that the model of this problem is a fuzzy mixed-integer nonlinear programming type and in order to solve it, a hybrid method of fuzzy simulation and genetic algorithm approach is used. At the end, a numerical example is given to demonstrate the applicability of the proposed methodology in real world inventory control problems.
  Ata Allah Taleizadeh , Seyed Taghi Akhavan Niaki and Seyed Vahid Hosseini
  This study points out the real-world prevalence of the multiple-product multiple-constraint Newsboy problem, i.e., the Newsstand problem, in which not only there are incremental discounts on the purchasing prices, but also the orders are placed in batch forms. The constraints are the service levels and warehouse capacity. Moreover, the quantities of the orders are integer multiples of packets, each containing more than one product. The objective of this problem is to find the order quantities such that the expected sum of the shortage, holding and purchasing costs is minimized. We assume that the holding and shortage costs occur at the end of the period; they are modeled by a quadratic function and that the decision variables are integer. We present a formulation to the problem and show that it is a integer nonlinear programming model. Finally, we provide an efficient algorithm to solve the new problem and illustrate the results with a numerical example.
  Seyed Taghi Akhavan Niaki and Mohammad Saber Fallah Nezhad
  In order to design a decision-making framework in production environments, in this study, we use both the stochastic dynamic programming and Bayesian inference concepts. Using the posterior probability of the production process to be in state λ (the hazard rate of defective products), first we formulate the problem into a stochastic dynamic programming model. Next, we derive some properties for the optimal value of the objective function. Then, we propose a solution algorithm. At the end, the applications and the performances of the proposed methodology are demonstrated by two numerical examples.
 
 
 
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