Showing 9 results for Ahmadi
H. Ahmadian, S. Nazari , H. Jalali ,
Volume 18, Issue 4 (International Journal of Engineering 2007)
Abstract
Abstract: The governing equations of motion for a drill string considering coupling between axial, lateral and torsional vibrations are obtained using a Lagrangian approach. The result leads to a set of non-linear equations with time varying coefficients. A fully coupled model for axial, lateral, and torsional vibrations of drill strings is presented. The bit/formation interactions are assumed to be related to the following parameters: bit motion, effects of gyroscopic moments, contact with the borehole wall, axial excitation due to bit/formation interactions, and hydrodynamic damping due to the presence of drilling mud. Simulation results show that parametric resonance and whirling may occur simultaneously within the range of operating conditions of drilling. The contact force between collar and borehole wall is calculated and its behavior is investigated. The dynamic behavior is quite complicated and may become non-periodic, suggesting a chaotic behavior.
N. Parvini Ahmadi, T. Czerwiec ,
Volume 19, Issue 5 (IJES 2008)
Abstract
Low temperature plasma assisted nit riding treatments of 316 stainless steel produce a complex layer constituted by tow different metastable f.c.c. solid solution denoted ( γ N1 and γ N2 ). About the formation of these double layers, different hypothesis was proposed in the literature. For verifying these hypotheses, the effects of differentes conditions such as nit riding temperature, cleaning and nit riding duration and cooling state have been studied. The results show that γ N2 sub layer produce during the ion bombardment cleaning procedure, before the nit riding treatment. Also the formation of the γ N2 layer is not connected to the cooling state of the sample after nit riding treatment.
Mona Ahmadi Rad, Mohammadjafar Tarokh, Farid Khoshalhan ,
Volume 22, Issue 1 (IJIEPR 2011)
Abstract
This article investigates integrated production-inventory models with backorder. A single supplier and a single buyer are considered and shortage as backorder is allowed for the buyer. The proposed models determine optimal order quantity, optimal backorder quantity and optimal number of deliveries on the joint total cost for both buyer and supplier. Two cases are discussed: single-setup-single-delivery (SSSD) case and single-setup-multiple-deliveries (SSMD) case. Two algorithms are applied for optimizing SSMD case: Gradient search and particle swarm optimization (PSO) algorithms. Finally, numerical example and sensitivity analysis are provided to compare the total cost of the SSSD and SSMD cases and effectiveness of the considered algorithms. Findings show that the policy of frequent shipments in small lot sizes results in less total cost than single shipment policy .
Mona Ahmadi Rad , Farid Khoshalhan,
Volume 22, Issue 2 (IJIEPR 2011)
Abstract
inventory model, backorder buyer , vendor, lot for lot policy |
In this paper, an inventory model for two-stage supply chain is investigated. A supply chain with single vendor and single buyer is considered. We assume that shortage as a backorder is allowed for the buyer and the vendor makes the production set up every time the buyer places an order and supplies on a lot for lot basis. With these assumptions, the joint economic lot size model is introduced and the minimum joint total relevant cost and optimal order quantity and optimal shortage quantity are obtained for both the buyer and the vendor at the same time. Numerical example is given and then Sensitivity analysis is performed to study the effects of changes in the parameters on optimum joint total relevant cost and optimal order quantity and optimal shortage quantity .
Seyed Omid Hasanpour Jesri, Abbas Ahmadi, Behrooz Karimi, Mohsen Akbarpour ,
Volume 23, Issue 4 (IJIEPR 2012)
Abstract
One of the most important issues in urban planning is developing sustainable public transportation. The basic condition for this purpose is analyzing current condition especially based on data. Data mining is a set of new techniques that are beyond statistical data analyzing. Clustering techniques is a subset of it that one of it’s techniques used for analyzing passengers’ trip. The result of this research shows relations and similarities in different segments that its usage is from strategic to tactical and operational areas. The approach in transportation is completely novel in the part of trip patterns and a novel process is proposed that can be implemented in highway analysis. Also this method can be applied in traffic and vehicle treats that need automatic number plate recognition (ANPR) for data gathering. A real case study has been studied here by developed process.
Masoud Mahootchi, Taher Ahmadi, Kumaraswamy Ponnambalam,
Volume 23, Issue 4 (IJIEPR 2012)
Abstract
This paper presents a new formulation for warehouse inventory management in a stochastic situation. The primary source of this formulation is derived from FP model, which has been proposed by Fletcher and Ponnambalam for reservoir management. The new proposed mathematical model is based on the first and the second moments of storage as a stochastic variable. Using this model, the expected value of storage, the variance of storage, and the optimal ordering policies are determined. Moreover, the probability of within containment, surplus, and shortage are computable without adding any new variables. To validate the optimization model, a Monte Carlo simulation is used. Furthermore, to evaluate the performance of the optimal FP policy, It is compared to (s*,S*) policy, as a very popular policy used in the literature, in terms of the expected total annual cost and the service level. It is also demonstrated that the FP policy has a superior performances than (s*,S*) policy.
Dr. Amin Vahidi, Dr. Alireza Aliahmadi, Dr. Mohammad Reza Hamidi, Dr. Ehsan Jahani,
Volume 26, Issue 3 (IJIEPR 2015)
Abstract
This paper offers an approach that could be useful for diverse types of layout problems or even area allocation problems. By this approach there is no need to large number of discrete variables and only by few continues variables large-scale layout problems could be solved in polynomial time. This is resulted from dividing area into discrete and continuous dimensions. Also defining decision variables as starting and finishing point of departments in area makes it possible to model layout problem so. This paper also provides new technique that models basic constraints of layout problems.
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Parviz Fattahi, Sanaz Keneshloo, Fatemeh Daneshamooz, Samad Ahmadi,
Volume 30, Issue 1 (IJIEPR 2019)
Abstract
In this research a jobshop scheduling problem with an assembly stage is studied. The objective function is to find a schedule which minimizes completion time for all products. At first, a linear model is introduced to express the problem. Then, in order to confirm the accuracy of the model and to explore the efficiency of the algorithms, the model is solved by GAMS. Since the job shop scheduling problem with an assembly stage is considered as a NP-hard problem, a hybrid algorithm is used to solve the problem in medium to large sizes in reasonable amount of time. This algorithm is based on genetic algorithm and parallel variable neighborhood search. The results of the proposed algorithm are compared with the result of genetic algorithm. Computational results showed that for small problems, both HGAPVNS and GA have approximately the same performance. And in medium to large problems HGAPVNS outperforms GA.
Seyedhamed Mousavipour, Hiwa Farughi, Fardin Ahmadizar,
Volume 30, Issue 3 (IJIEPR 2019)
Abstract
Sequence dependent set-up times scheduling problems (SDSTs), availability constraint and transportation times are interesting and important issues in production management, which are often addressed separately. In this paper, the SDSTs job shop scheduling problem with position-based learning effects, job-dependent transportation times and multiple preventive maintenance activities is studied. Due to learning effects, jobs processing times are not fixed during plan horizon and each machine has predetermined number of preventive maintenance activities. A novel mixed integer linear programming model is proposed to formulate the problem for minimizing Make Span. Owing to the high complexity of the problem; we applied Grey Wolf Optimizer (GWO) and Invasive Weed Optimizer (IWO) to find nearly optimal solutions for medium and large instances. Finally, the computational Results are provided for evaluating the performance and effectiveness of the proposed solution approaches.
