

Articles
by
Seyed Taghi Akhavan Niaki 
Total Records (
3 ) for
Seyed Taghi Akhavan Niaki 





Ata Allah Taleizadeh
,
Seyed Taghi Akhavan Niaki
and
MirBahador Aryanezhad


While in multiperiodic 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 integertype and that there are space, budget and service level constraints, incremental discount is considered to purchase products and a combination of backorder and lostsales are taken into account for the shortages. We show that the model of this problem is a fuzzy mixedinteger 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 realworld prevalence of the multipleproduct
multipleconstraint 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 decisionmaking 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. 





