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Cutoff grade is a grade used to assign a destination label to a parcel of material. The optimal cutoff grades depend on all the salient technological features of mining, such as the capacity of extraction and of milling, the geometry and geology of the orebody, and the optimal grade of concentrate to send to the smelter. The main objective of each optimization of mining operation is to maximize the net present value of the whole mining project, but this approach without consideration of environmental issues during planning is not really an optimum design. Lane formulation among the all presented algorithms is the most commonly used method for optimization of cutoff grades. All presented models for optimum cutoff grades are ore-oriented and in none of them the costs related to waste materials which must to be minimized during the mine life are considered. In this paper, after comparison of traditional and modern approaches for cutoff grade optimization in open pit mines, a real case study is presented and discussed to ensure optimality of the cutoff grades optimization process.

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  One of an important factor in the success of organizations is the efficiency of knowledge flow. The knowledge flow is a comprehensive concept and in recent studies of organizational analysis broadly considered in the areas of strategic management, organizational analysis and economics. In this paper, we consider knowledge flows from an Information Technology (IT) viewpoint. We usually have two sets of technological challenges that prevent the knowledge flow efficiency in the organizations: the passive kind of present knowledge management technologies and the information excess problem. To get the efficient flow of knowledge, we need high exactness recommender systems and dynamic knowledge management technologies that automate knowledge transportation and permit the management and control of knowledge flow . In this paper, we combine and make upon the information management systems and workflows presented in literature to generate technologies that address the serious gap between current knowledge management systems. Also, we propose a knowledge management framework for educational organizations and use this framework in a real situation and analyze the results. The weakness of knowledge flow infrastructure is one of the most important barriers to knowledge sharing through an organization. The proposed technology in this paper provides a new generation of knowledge management systems that will permit the efficient flow of knowledge and conquest to the technological constraints in knowledge sharing across an organization .

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Abstract Profile monitoring in statistical quality control has attracted attention of many researchers recently. A profile is a function between response variables and one or more independent variables. There have been only a limited number of researches on monitoring multivariate profiles. Indeed, monitoring correlated multivariate profiles is a new subject in the fileld of statistical process control. In this paper, we investigate the effect of autocorrlation in monitoring multivariate linear profiles in phase II. The effect of three main models namely AR(1), MA(1), and ARMA(1,1) on the methods of multivariate linear profile monitoring is evaluated and compared by using simulation study and average run length criteria. Results indicate that autocorrelation affects performance of the existing methods significantly.

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Allocation of construction risks between clients and their contractors has a significant impact on the total construction costs. This paper presents a system dynamics (SD)-based approach for quantitative risk allocation. Using the proposed SD based approach, all the factors affecting the risk allocation process are modeled. The contractor’s defensive strategies against the one-sided risk allocation are simulated using governing feedback loops. The full-impact of different risk allocation strategies may efficiently be modeled, simulated and quantified in terms of time and cost by the proposed object-oriented simulation methodology. The project cost is simulated at different percentages of risk allocation and the optimum percentage of risk allocation is determined as a point in which the project cost is minimized. To evaluate the performance of the proposed method, it has been implemented in a pipe-line project. The optimal risk allocation strategy is determined for the inflation risk as one of the most important identified risks.

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The concept of "complexity" is familiar to most of project's managers, but it is not comprehended in the same way. although the complexity highlights negative points, but it may bring positive advantages which support the project. Researches conducted on this field show that the understanding of "complexity" between the researchers is different and it is mainly depends on their points of view. In fact, many identified aspects of the complexity in the literature are related to the aims of the research. In this paper, an attempt was made to describe the positive / negative features of the complexity of project using three approaches research literature (manufacturing and project complexity), interviews (deep interview with 20 experts) and questionnaire. The research was conducted on the Complex product and system (CoPS) projects. in addition, WH question technique was used. In conclusion, a 5p model (Purpose, Product, Process, People, Peripheral) has been introduced as the outcome of the study.

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Efficiency and effectiveness of the organization is result ofmanagement performance and supply chain structure.Today, several factors in selection the supplier or the best combination of suppliers have been identified that this issue would increase the complexity of suplier selecting.This study investigates the application of Fuzzy Delphi in order to identify the important factors in selecting a supplier in the steel industry and then provide a comprehensive and holistic model of supplier selection to overcome the complexity.In this context, Interpretive Structural Modeling (ISM) unlike other methods, the holistic, dealing with supplier selection to prioritize components-surfacing and identifying key components, so industry leaders will provide comperhensive map to select the best combination based on their.The results of this study indicate that "technically possible", "financial health" and "geography situation" are the basic components to the selection of suppliers.

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Health care centers as an important part of health care industry, in addition to following their major mission, that is, providing high quality health service, can gain environmental and even socioeconomic advantages through reducing environmental effects resulted from their activities. With the goal of gaining these advantages, health care centers can increase their environmental performance through adopting a systematic and proper approach in application of information systems (ISs). The Green information systems (ISs) that indicate a novice approach in application of ISs are considered as necessary tools to realize the goals of environmental sustainability. Different factors affect Green ISs adoption by health care centers. In this research, these factors were first identified through library method and review of the literature. Then, the relationships between these factors were analyzed and modeled using interpretive structural approach. According to the results, the volume of social investment, research and development along with the senior management’s insight and commitment are the most important factors affecting Green ISs adoption in the health care centers.

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In order to manage a project with integrity, a cohesive communication is needed between its various sections; possible risks, identification of stakeholders, providing the necessary resources on time and managing their availability, focusing on the approved budget and satisfactory quality the project can be successfully done. In the recent year BIM has as new aspects to engineering and architecture, and has become an accepted platform for planning and executing construction projects and contributed to integration of various fields and. also, project management standards, such as PMBOK, have come to aid construction managers. Through the basic capacities of BIM, and questionnaires according to aspects of PMBOK, the present study tries to identify the superior effects of BIM on project management. Moreover, it seeks to recognize the most significant aspects of BIM application on project management. by employing the FANP-AVIKOR decision making method to prioritize the parameters of the collected results, the study’s conclusion will indicate that almost all of PMBOK aspects equally benefit from using BIM; in addition, it will show that 3D BIM capacities, including clash detection, plan correction, are superior in comparison with 6D BIM and 7D BIM capacities.

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Nowadays, Military products of superpowers countries have a high level of diversity, delivery speed, and appropriative operational functionality. Therefore, Production of varied, high quality and high speed delivery military products, is essential for enhance Iran's defensive deterrence power.
Defense industries supply chain agility is an answer to how to produce military products with these features. This paper, with the aim of providing supply chain agility model in defense industries, first, identifies the most important supply chain agility practices, Then, using factor analysis, categorizes the practices and validates them based on structural equation modeling (SEM) and finally, using Interpretative Structural Modeling (ISM), presents a model that shows the relationships and hierarchy between these practices. The results show that out of a total of 62 practices introduced in the previous research for agile supply chain, 41 practices in the agility of the supply chain of defense industries are effective. These practices were classified in 8 categories include supplier relationship, workshop level management, organizational structure improvement, human resource management, product designing, improve and integrate the process, application of information technology, and customer relationship. Improvement of organizational structure was at the lowest level of the model. Therefore, managers first should focus on it.
 

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The results of studies on the development of new statistical and econometric approaches to modeling budget policy is presented. The obtained results are applied on the example of tax revenue modeling. The authors note the importance of ensuring transparency and predictability of state financial policy, the realisticness of economic forecasts, because this is the basis of budget modeling. It is also necessary to take into account the various economic cycles that affect the economic dynamics in a particular period of time and in a particular country (or group of countries). Accounting for various factors, including through the use of mathematical methods, will allow to plan reforms with a scientific position. In particular, this is especially true in connection with the introduction of multi-year budget planning. The most important issue of budget policy is the planning of tax revenues (taxes form 90% of budget revenues). To identify the main threats to the tax base, the phenomenon of “tax passes” was used, which is based on an assessment of the effectiveness of a tax credit. The main participants in the formation of the “gross gap” in the value added tax revenues in Ukraine are shown. A correlation and regression analysis of the natural logarithms of the gross domestic product and tax revenues is carried out. This allowed us to determine the elasticity of tax revenues and GDP in Ukraine. A change in GDP directly affects the amount of tax payments to the budget, and the rate of change of indicators is proportional and changes insignificantly. These results allow us to strategically model the reform of discretionary tax policy mechanisms based on a quantitative assessment of tax gaps and the elasticity of tax payments. The authors were able to substantiate some proposals for reforming the budget policy regarding tax revenues.

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This study seeks to introduce the influential factors in controlling and dealing with uncertainty in intermittent demand. Hybrid forecasting and Grey Theory, due to their potential in facing complex nature, insufficient data, have been used simultaneously. Different modeling, unbiased weighting results have been used in estimating the safety stock(SS) by both theoretical and experimental methods. In other words, this work deals with the less studied feature of various modeling errors and their effect on SS determination and recommends its use to address the uncertainty of intermittent demand as a criterion for introducing a superior model in the field of inventory.

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Given the increasing human need for health systems and the costs of using such systems, the problem of optimizing health-related systems has attracted the attention of many researchers. One of the most critical cases in this area is the operating room scheduling. Much of the cost of health systems is related to operating room costs. Therefore, planning and scheduling of operating rooms can play an essential role in increasing the efficiency of health systems as well as reducing costs. Given the uncertain factors involved in such matters, attention to uncertainty in this problem is one of the most critical factors in the results. In this study, the problem of the daily scheduling of the operating room with uncertain surgical time was investigated. For minimizing overhead costs and maximizing the number of surgeries to reduce patients' waiting time, after introducing a mathematical model, a chance-constrained programming approach is used to deal with its uncertainty. In this study, also, a harmony search algorithm is proposed to solve the model because of its NP-Hardness. By performing the numerical analysis and comparing the presented algorithm result with a genetic algorithm, the results show that the proposed algorithm has a better performance.

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