Sharif Digital Repository

In this study, a multi-item economic order quantity model with shortage under vendor managed inventory policy in a single vendor single buyer supply chain is developed. This model explicitly includes warehouse capacity and delivery constraints, bounds order quantity, and limits the number of pallets. Not only the demands are considered imprecise, but also resources such as available storage and total order quantity of all items can be vaguely defined in different ways. An ant colony optimization is employed to find a near-optimum solution of the fuzzy nonlinear integer-programming problem with the objective of minimizing the total cost of the supply chain. Since no benchmark is available in... 

The purpose of this paper is to develop a multi-item economic order quantity (EOQ) model with shortage for a single-buyer single-supplier supply chain under green vendor managed inventory (VMI) policy. This model explicitly includes the VMI contractual agreement between the vendor and the buyer such as warehouse capacity and delivery constraints, bounds for each order, and limits on the number of pallets. To create a kind of green supply chain, tax cost of green house gas (GHG) emissions and limitation on total emissions of all items are considered in the model. A hybrid genetic and imperialist competitive algorithm (HGA) is employed to find a near-optimum solution of a nonlinear... 

Recent researches have shown the importance of improving the supply chain competitiveness by means of strategic alliances. This study considers the retailer-supplier partnership through a vendor-managed inventory (VMI) system and develops an analytical model to explore the effect of important supply chain parameters on the cost savings realized from collaborative initiatives. This model is developed for a two-level supply chain consisting of a single supplier and a single retailer and examines the inventory management practices before and after implementation of VMI. The results of analytical examination show that VMI implementation in economic order quantity model when shortage is... 

The purpose of this research is to explain the surface modification of fabricated polyamide reverse osmosis (RO) membranes using UV-initiated graft polymerization at different irradiation times (15, 30, 60, and 90 s) and various acrylamide concentrations (10, 20, and 30 g L−1). Also, coating of membranes surface with various concentrations of TiO2 nanoparticles (10, 20, 30, and 50 ppm) followed by the same UV irradiation times was investigated. After that, the membranes modification was done by grafting of acrylamide blended with TiO2 nanoparticles via UV irradiation. The characterization of membranes surface properties and their performance were systematically carried out. The results... 

An optical amplifier followed by a bistable element has been statistically analyzed before [1]. In this manuscript, output noise analysis represents, then signal to noise ratios (SNR) are calculated either for input or output. It will be shown that noise reduction, can be achieved by a proper selection of parameters  

Control Performance Assessment (CPA) and tuning of PID controllers are studied in this paper. We propose a framework for systematic analysis of the tradeoff between the structural complexity of the controller and its performance. As the measure of the controller performance, an LQG based index is used. The problem is augmented with an additional term which forces sparsity on the complexity of a decentralized PID controller. The desired complexity is controlled via a weighting parameter which determines the cost of each additional element (i.e., P, I, and D terms). The result is a decentralized multivariable PID controller in which the complexity of each loop controller is optimized such that... 

Control Performance Assessment (CPA) and tuning of PID controllers are studied in this paper. We propose a framework for systematic analysis of the tradeoff between the structural complexity of the controller and its performance. As the measure of the controller performance, an LQG based index is used. The problem is augmented with an additional term which forces sparsity on the complexity of a decentralized PID controller. The desired complexity is controlled via a weighting parameter which determines the cost of each additional element (i.e., P, I, and D terms). The result is a decentralized multivariable PID controller in which the complexity of each loop controller is optimized such that... 

One of the distributed solutions for scaling Web Search Engines (WSEs) may be peer-to-peer (P2P) structures. P2P structures are successfully being used in many systems with lower cost than ordinary distributed solutions. However, the fact that they can also be beneficial for large-scale WSEs is still a controversial subject. In this paper, we introduce challenges in using P2P structures to design a large-scale WSE. Considering different types of P2P systems, we introduce possible P2P models for this purpose. Using some quantitative evaluation, we compare these models from different aspects to find out which one is the best in order to construct a large-scale WSE. Our studies indicate that... 

Crack detection is a vital component of structural health monitoring. Several computer vision-based studies have been proposed to conduct crack detection on concrete surfaces, but most cases have difficulties in detecting fine cracks. This study proposes a deep learning-based model for automatic crack detection on the concrete surface. Our proposed model is an encoder–decoder model which uses EfficientNet-B7 as the encoder and U-Net’s modified expansion path as the decoder. To overcome the challenges in the detection of fine cracks, we trained our model with a new training strategy on images extracted from an open-access dataset and achieved a 96.98% F1 score for unseen test data. Moreover,... 

Crack detection is a vital component of structural health monitoring. Several computer vision-based studies have been proposed to conduct crack detection on concrete surfaces, but most cases have difficulties in detecting fine cracks. This study proposes a deep learning-based model for automatic crack detection on the concrete surface. Our proposed model is an encoder–decoder model which uses EfficientNet-B7 as the encoder and U-Net’s modified expansion path as the decoder. To overcome the challenges in the detection of fine cracks, we trained our model with a new training strategy on images extracted from an open-access dataset and achieved a 96.98% F1 score for unseen test data. Moreover,...