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Most of data in a multi attribute decision making (MADM) problem are unstable and changeable, and thus sensitivity analysis can effectively contribute to making proper decisions. Here, we offer a new method for sensitivity analysis of multi-attribute decision making problems so that by changing one element of decision making matrix, we can determine changes in the results of a decision making problem. An analysis is made for simple additive weighting method (SAW) technique, a mostly used multi-attribute decision making techniques, and the corresponding formulas are obtained.

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In traditional data envelopment analysis (DEA) the uncertainty of inputs and outputs is not considered when evaluating the performance of a unit. In other words, effects of uncertainty on optimality and feasibility of models are ignored. This paper introduces a new model for measuring the efficiency of decision making units (DMUs) having interval inputs and outputs. The proposed model is based on interval DEA (IDEA) in which the inputs and outputs are limited to be within uncertainty bounds. In this model, the inputs and outputs take fixed values for each DMU such that the sum of efficiencies is maximized. The DMUs are evaluated by the same production possibility set (PPS). The efficiency is measured based on the proposed conservatism level for each input and output. Indeed, the inputs and outputs are defined by the presented conservatism level. The proposed model is integrated measuring all the DMUs efficiencies simultaneously. These efficiency scores lie between the optimistic and pessimistic cases introduced by Despotis and Similar (2002) [11].

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In third world countries, organizational leaders rarely have figured out to consider happiness and joy of work as a part of the system they are managing. Usually, happiness in organizations is not considered as a management style. Gradually, it became obvious that joy and fun at the workplace will decrease the health care costs, enhances the customers’ loyalty, and increases productivity and profits as a result. Most research on this subject matter relied upon very specific case studies. No research exits dealing with the risks and benefits of Joyful organization. The objectives of this paper are twofold: (1) to utilize hierarchical fuzzy technique for order preference by similarity to ideal solution (TOPSIS) to determine the most suitable type of Joyful Organization (JO), and (2) to list key risks and benefits of Joyful Organization. This researcher explains the importance of selection criteria for evaluation of Joyful organizations. It provides key elements on JO, Quantitative strategic planning matrix (QSPM), and fuzzy hierarchical TOPSIS methodology. Since QSPM is used with SWOT by many practitioners and researchers in various fields of study, it was selected as a tool for validation purposes. A case study is taken under consideration and results are explained for both approaches.  The finding of this research points to the suitability of semi conventional organization strategy which means implementing about 50% of the rules of main cultural organizations. A sensitivity analysis was performed on TOPSIS using the weights generated by the hierarchical fuzzy TOPSIS approach, Shannon entropy weight, and TOPSIS approach. The ranking results obtained are identical for all these three cases.
 

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Abstract
Urban land allocation, planning and management are a complicate problem challenging the decision makers and policy writers all around the Word. The multi objectivity nature of the problem has engaged researchers to deal with the environmental, ecological, economical, social, recreational, commercial, and residential problems simultaneously, in any region, for better decision making. These modelers neglected to consider people’s satisfaction and wellbeing due to land allocation, planning, and development. Complex problems as such as land allocation and planning are in need of suitable integrated model building for solution and analysis. It was to this end that this author proposes a system dynamics approach for studying the impacts of the decisions made, by the policy makers in the long run, on the community’ satisfaction using computer simulation. Taking one land allocation decision into consideration, the results of our proposed dynamic modeling points to this reality that people’s level of satisfaction improves, their level of incomes enhance, and the quality of their lives increases with the passage of time.
 

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With this research, author presents an understanding of business value that would be enhanced by adopting a new technology into the system. A healthcare center is the case here and the technology considered is radio frequency identification (RFID). To present such framework for evaluation purposes, a two phase analysis is introduced. In the first phase and with the help of a multi attribute decision making in the context of hierarchical fuzzy TOPSIS, an RFID-based system among a set of proposed RFID based-systems are selected. In the second phase, with the help of system dynamics approach, the behaviors of system for goal variables are determined. To fully understand this approach, a sample case is provided and analyzed. This type of integrated decision-making approach can provide a deep understanding of the system because of providing one or more trends on key system variables based upon the optimal decision made at the present time using an MADM tool.  Due to the fact that this research combines four fields of knowledge into an interesting research problem, of highly concerned to the users, it makes a true contribution to health, system dynamics, RFID and MADM. Integration of MADM and SD approaches in healthcare system has some very important benefits for healthcare managers. It allows managers in seeing the system behaviour now under the decision made at the present time using multi attribute decision making approach.

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The biggest issue facing both industrialized and emerging nations these days is traffic congestion, which has changed people's perspectives on public transportation systems and accelerated efforts to make them more efficient. Urban traffic issues are a result of various factors, including population growth and the rise in private vehicle ownership. Urban public transportation is currently one of the primary strategies for reducing urban traffic congestion. Building simulation models allows for a more precise analysis of the basic capacity of buses at transfer stations on a given route, trip frequency, passenger behavior, and waiting times. This study suggests using a digital twin design to plan bus routes, reduce wait times for passengers, maximize bus frequency, and investigate the relationship between overall traffic flow and passengers. The Anylogic package program was utilized, which is a helpful tool for digital twin modeling and multi-method simulation. The usefulness of the digital twin concept—which links the physical and virtual worlds—was highlighted in determining the ideal number of trips and trip intervals as a result of the examinations made with the model's outputs. This allows for the instantaneous monitoring and storing of data in its physical conditions.