There are some problems with estimating the time required for the manufacturing process of products, especially when there is a variable serving time, like control stage. These problems will cause overestimation of process time. Layout CONSTRAINTS, reworking CONSTRAINTS and inflexible product schedule in multi product lines need a precise planning to reduce volume in particular situation of line stock. In this article, a hybrid model has been presented by analyzing real queue systems with layout CONSTRAINTS as well as by using concepts and principles of Markov CHAIN in queue theory. This model can serve as benchmark to assess queue systems with probable parameters of service. Here, the proposed model will be described drawing on the findings of a case study. Thus, production lines of a home application manufacturer will be analyzed.

Manufactures and service provider institutes usually need queue theory to optimize their decisions about customers' waiting time. This will help them to specify resources that should be investigated and also to provide customers' satisfaction. These two factors, resource allocation and customer satisfaction are so important for companies' survival essentially in a highly competitive environment. So describing queue systems performance in different environmental conditions is necessary. In this paper by analyzing actual queue systems with layout CONSTRAINTS, a framework is introduced for specific conditions by using Markov CHAIN concepts. This model can be a base for evaluating exponential queue systems with probability parameters. In this paper by providing a case study, it is tried to describe the proposed model. To do this, filling stations are analyzed.

The purpose of this study is to analyze the risk in the supply CHAIN with financial CONSTRAINTS and financial performance. The statistical population of this study is the managers, accountants and financial experts of companies active in the Tehran Stock Exchange in the field of food that are active in 1399. This research is based on the structural equation model in which the supply CHAIN risk variable includes four components of supplier risk, producer risk and distributor risk and end customer risk, financing constraint variable includes price and non-price CONSTRAINTS and The financial performance variable has three components: cost management, risk management and value management. These questionnaires were sent randomly to 230 people, out of which 201 questionnaires that were fully answered all questions were returned. Using the equations of structure and software of Emos, the validity and reliability of the questionnaire were confirmed and the hypotheses of this research were evaluated and evaluated. The results of this study show that risk in the supply CHAIN is related to financial CONSTRAINTS and financial performance and the relationship between supply CHAIN risk and financial performance is negative and significant and positively and significantly related to financial CONSTRAINTS.

This paper designs a mathematical model for supply CHAIN network design problem including plants, distributors and customers in fuzzy environment. Each plant and distributor has several levels capacities. A multi-mode demand strategy is considered for the customers where only one of the modes is to be selected for each customer. Considering the acceptance degree of fuzzy CONSTRAINTS violated, a method for solve the problem is proposed. For this aim, we proposed an order relationship for trapezoidal fuzzy numbers using their interval expectation value. According to this order relationship, the fuzzy supply CHAIN network problem is converted to an interval supply CHAIN network problem. Then, by combining the order relationship between intervals and acceptance degree of fuzzy CONSTRAINTS violated, the problem is transformed into a bi-objective program model and is solved by the global criterion method. Finally, in order to, show the effectiveness of the proposed approach, several test problems are solved in various sizes.

In today competitive environment, increasing supply CHAIN efficiency has considerable importance in success of firms. Various factors limit this increase, which are referred as supply CHAIN complexities. Identification of these complexities and dealing with them is essential. This paper attempts to introduce and apply an efficient and effective method for dealing with complexity of supply CHAIN. This method is based on systemic principles of theory of CONSTRAINTS. This research shows how a manager can use logical tools of theory of CONSTRAINTS thinking processes (TOC TP) to identify and deal with root causes of supply CHAIN complexity. This approach was implemented partially in a paper manufacturing firm in Iran. Data were gathered by questionnaires and interviews and analyzed interactively with supply CHAIN managers and experts of the firm in order to get valid results. In this case, three first steps of TOC TP i.e. drawing intermediate objective (IO) map, current reality tree (CRT) and conflict remove diagram (CRD) are performed. The results show that these logical diagrams are useful tools to identify supply CHAIN complexity drivers and determine root causes of them.

The importance of remanufacturing used products into new ones has been widely recognized in the literature and in practice. This is due to both of economic opportunities and environmental aspects. This paper aims to design a new integrated multi-period & multi-product closed-loop supply CHAIN network considering reused cost and capacity CONSTRAINTS for all stages. In this problem the stages of supplier, assembler, retailer, customer, collection center, refurbishing center, and disassembler is regarded consequently. The considered objective function is total cost factors that consists of 7 components: costs of associated with locating the plants and retailers, purchasing, transportation, collection of used products from customers, disposal for subassemblies, refurbishing, and finally refund to customers. First, parameters and decision variables of this problem are defined, then a mixed integer linear programming mathematical model is presented. The proposed mathematical model is run applying the GAMS software. Two real examples (shed light, and power-outlet) are considered to solve using the proposed mathematical model. These two examples were obtained based on data in two new references. Since this problem is known as NP-Hard, the model is run just for small-sized problem consists of four suppliers, two disassemblers, two retailers, and two periods. The results are analysed and some sensitivity analysis have been done for the effective factors. These result show that, the demand has a less effect on total cost. But Purchasing/refurbishing cost ratio has a high effect on the objective function. Finally, the capacity of collection and refurbishing centers has a high effect in primary changes and this effect gradually reduced. So having the proper capacity for collection and refurbishing centers and also creating balance between different stages can reduce overall cost.

In this paper, a bi-objective multi-product single-vendor single-buyer supply CHAIN problem is studied under green vendor-managed inventory (VMI) policy based on the economic production quantity (EPQ) model. To bring the model closer to realworld supply CHAIN, four CONSTRAINTS of model including backordering cost, number of orders, production budget and warehouse space are considered stochastic. In addition to holding, ordering and backordering costs of the VMI CHAIN, the unused storage space cost is also added to the total cost of the CHAIN. To observe environmental requirements and decrease the adverse effects of greenhouse gases emissions (GHGs) on the earth and human’ s life, green supply CHAIN is utilized to reduce the GHGs emissions through storage and transportation activities in the second objective function. Three multi-objective decision making methods namely, LP-metric, Goal attainment and multi-choice goal programming with utility function (MCGP-U) are implemented in different sizes to solve the presented model as well. Two multi-criteria decision making (MCDM) approach and statistical analysis are applied to compare the outcomes of three proposed solving methods. GAMS/BARON software is utilized to minimize the values of the objective functions. At the end, numerical examples are presented to represent the application of the mentioned methodology. To come up with more insights, sensitivity analysis is executed on the main parameters of proposed model.

Background and Aim: Culture and specific staining (including Zeil-Nelson and fluorescent methods) are standard measures for the diagnosis of tuberculosis (TB). Because these methods are time-consuming and, sometimes, due to their low accuracy faster and more accurate methods are necessitated. Methods, which can substitute invasive procedures, when obtaining smear samples and culture is not possible, and in addition to being simple and fast, they have an acceptable diagnostic accuracy.The aim of the present study was to verify the diagnostic value of blood Polymerase CHAIN Reaction (PCR) method in pulmonary TB.Materials and Methods: This case-control study included 64 proven pulmonary TB cases (according to The National TB Protocol) and 28 subjects who were completely healthy. 4.5ml of blood was derived from each participant and then mixed with 0.5ml EDTA. Finally, DNA extraction and PCR testing using SI 6110 primers was performed for all blood samples.Results: Mean age of the cases and controls was 49.8±18.6 and 48.2±18.5, respectively. 49.2% of the cases and 25% of controls were male. Blood PCR in 23 patients with TB was positive, but none of the controls had a positive PCR (thus, sensitivity of 35.7% and specificity of 100%).Conclusion: With regard to specificity of 100% in PCR method (despite its low sensitivity), in conditions where there is no access to an appropriate specimen, a positive blood PCR can obviate invasive procedures and rapid and definitive diagnosis of the disorder and timely treatment of the patient, his life is saved.