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The degree of effectiveness of information technology (IT) in industry and the way it aids organizational goals are considered as very key sensitive points in industry's communications and interactions in the worldwide scale. In fact information technology has got various functions in different sectors of industry most of which are not simply quantifiable. Usually a large quantity of the information we deal with in industrial atmospheres are ambiguous and in a way fuzzy. That's why it makes it almost impossible to utilize common ways of decision-making in this area. In this research due to integrity of decision-making approach, evaluation of information technology will be based on FAHP and BSC approaches. Ways forward for BSC to express organizational hierarchy are divided into four main sections (financial, buyer, the function's internal process, and training & rate of progress). These factors are considered as functional indicators for each section to be evaluated. The FAHP approach here is mainly advised to be used to clarify the ambiguity of the information. In conclusion this integrated methodology facilitates planning in information systems and gives some clues to create a viable system of information technology in industry. That means provision of ways forward for improvements in performance of information technology in Industries.

Integrating strategic and tactical decisions to location-allocation and green inventory planning by considering e-commerce features will pave the way for supply chain managers. Therefore, this study provides an effective framework for making decisions related to different levels of the dual-channel supply chain. We provide a bi-objective location-allocation-inventory optimization model to design a dual-channel, multi-level supply chain network. The main objectives of this study are to minimize total cost and environmental impacts while tactical and strategic decisions are integrated. Demand uncertainty is also addressed using stochastic modeling, and inventory procedure is the periodic review . We consider many features in inventory modeling that play a very important role, such as lead time, shortage, inflation, and quality of raw materials, to adapt the model to the real conditions. Since a dual-channel supply chain is becoming more important for sustainable economic development and resource recovery, we combine online and traditional sales channels to design a network. We generate five test problems and solve them by using the augmented ε-constraint method. Also, the Grasshopper optimization algorithm was applied to solve the model in a reasonable time for a large size problem. In order to provide managerial insights and investigate the sensitivity of variables and problem objectives with respect to parameters, sensitivity analysis was performed.

This paper models supply chain uncertainties by fuzzy sets and develops a fuzzy linear programming model for tactical supply chain planning in a multi-echelon, multiproduct, multi-stage with different methods of manufacturing in each stage, multidistribution centre and multi-period supply chain network. In this approach, the demand, process and supply uncertainties are jointly considered. The aim is to achieve the best use of the available resources and the best method of manufacturing at each stage for a product along the time horizon so that customer demands are met at a minimum cost. The fuzzy model provides the decision maker with alternative decision plans with different degrees of satisfaction.

Studying and improving health care services levels are considered as an essential issue in urban management systems and also crisis management. In such areas, detecting effective factors, managing the relationships, control of costs, defining and planning for health care services resources are significance. In current paper, by analyzing the patients' behavior in one hospital unit, development and optimization of the mentioned unit's performance and defining the optimum resources have been studied. In order to modeling of the study, simulation software ExtendSim has been used. By implementing the outcome of the study and optimization of the hospital resources, waiting time for the patients could be reduced significantly, and also the related costs can be controlled properly.

In this article it has been tried to show that fuzzy theory performs better than probability theory in monitoring the product quality. A method that uses statistical techniques to monitor and control product quality is called statistical process control (SPC), where control charts are test tools frequently used for monitoring the manufacturing process. In this study, statistical quality control and the fuzzy set theory are aimed to combine. As known, fuzzy sets and fuzzy logic are powerful mathematical tools for modeling uncertain systems in industry, nature and humanity; and facilitators for common-sense reasoning in decision making in the absence of complete and precise information. In this basis for a textile firm for monitoring the yarn quality, control charts according to fuzzy theory by considering the quality in terms of grades of conformance as opposed to absolute conformance and nonconformance. And then with the same data for a textile factory, the control chart based on probability theory is constructed. The results of control charts based on two different approaches are compared. It's seen that fuzzy theory performs better than probability theory in monitoring the product quality.

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The process of planning, scheduling and economizing of new project is getting more difficult. Considering lack of raw materials, strict standards and tough competition, taking the right decision is not a simple task any more. In the process of globalization, only companies will be successful which are able to commercialize their dream with controlling effecting factors. Financial, operational and time bonded factors which sometimes follow accidental trends. Considering the probability behavior of this factors, benefiting from simulation approach to formulate the effect of these factors are one of the main solutions. Therefore under follow article we use simulation methodology to evaluate R&D projects, affected by accidental factors. Bearing in mind with more repeat we minimize the mistakes in project and get to the optimize answer. To evaluate the projects, a financial model is being presented, including sales quantity and price to calculate the profit. Total cost is being calculated based on unit cost. To find the best answer we repeat the model more than 800 times with the help of Ant colony optimization algorithms. To elaborate on model, we have studied an operational unit and will show the sensitivity and analysis of model. Later we will see the result with the help of diagrams.