فهرست مطالب morteza khakzar bafruei

The present study has developed a dynamic model of bank strategy in uncertainty using the system dynamics approach. After examining the Iran's banking system and Detection of future uncertainties with the participation of policymakers of Saderat bank, a causal diagram of the banking system's performance in conditions of uncertainty was designed. The Dynamic accumulation and flow model was designed based on banking data and simulated over a 20-year horizon. After validation of the model, based on the results of sensitivity analysis, bank strategies and policies were extracted and analyzed in conditions of uncertainty. According to the research findings, four strategies of managing the bank's assets and expenses, attracting financial resources and profitability, empowering the bank's management and developing the banking infrastructure, as well as selected combinations were identified and simulated. As a result, the selected Strategy simulation is a combination of policies, show the best perfomance including: 1-three times increase in investment in banking infrastructure; 2- Creating special mechanisms for collection of receivables; 3- Managing a 5% reduction in bank costs through streamlining processes and empowering human resources, as well as monitoring the bank's costs and expenses. 4- Increasing 4 times the efficiency of the appropriate accreditation process for customers. Financial transparency reports and effective communication with key stakeholders were provided. 5- Twice the increase of depositors' trust and security by presenting financial transparency reports and effective communication with key stakeholders, which as a result of applying these strategies, improves the bank's profitability, increases receivables and reduces costs. We will be.

The present study explains a dynamic model for developing the performance of the Iranian banking system.

first, by examining the country's economic trend, uncertainties affecting the performance of the banking system based on international indicators of CAMELS were identified, and the network of uncertainties in the Iranian banking system to determine critical uncertainties using the approach SNA was evaluated. In the next stage, the dynamic model of the banking system performance in uncertainty conditions was designed using the SD based on the data of Bank Saderat Iran, and the model was simulated over a 20-year horizon.

According to the research findings, four strategies of bank assets and costs management, the attraction of financial resources and profitability, bank management empowerment and banking infrastructure development, and a selected mixed strategy were identified and simulated, which includes 1- increase investment in banking infrastructure, 2- Create special mechanisms for collecting receivables, 3- Manage bank costs by the agility of processes and empower human resources, as well as monitor the bank's costs, 4. Increase the efficiency of the appropriate customer validation process, 5. Increase the trust and security of depositors by providing financial transparency reports and effective communication with key stakeholders.

Originality / Value: 

Reforming the structure of the banking system, formulating efficient monetary and financial policies and regulations, and effective supervision of the country's banks can transfer uncertainties to the banks with less severity, and only in this situation can banks develop their performance with long-term planning.

Over the past two decades, especially after the events of September 11, 2001, the security game research area has been at the center of attention of researchers, and the scientific publications in this area have grown increasingly. The present study is done to examine the situation and science mapping of publications in security game research area, especially in the field of engineering,  and furthermore, intends to create an insight into this field for future research. The statistical population of this study is the journal papers written in English that have been published in the Scopus Scientific Database. In this study, for the first time in the field of systematic reviewing the security game literature, a bibliometric analysis approach has been used, adopting Bibexcel and Gephi software. Analytical results of the subject of co-citation network of highly cited references show that the problem of optimization of defensive resource allocation to the infrastructures and information and communication security are the main subject areas, which have been addressed in the examined papers. This suggests that, given the wide range of different types of strategic assets exposed to different types of threats, there is now much potential to address the security game in the field of engineering. Finally, after reviewing the content of the first cluster’s papers, which deals with the allocation optimization of defensive resources based on game theory approach, some suggestions for future research on the problem in the field of engineering are presented.

Statistical process control and maintenance management are two key tools for controlling production processes. However, These two tools are traditionally separated (both in science and in business practice), their goals overlap a great deal. Their common goal is to achieve optimal product quality, little downtime and cost reduction by controlling variances in the process, that achieving these goals will increase the level of reliability of product quality. Using these two tools together can have better performance in terms of cost and quality for the organization; Therefore, in this research, an integrated model of statistical process control and maintenance management has been designed by considering the costs of two tools in Kish Wood Industries Company. The optimization criterion is to minimize the average total cost per unit time of these two systems. For this purpose, from MATLAB software and grid search approach to find the optimal values of sampling size (n), width of control limits (L), sampling interval (h) and number of sampling times during the planned maintenance (k) is used.The values of n, h, L and k for the laminating process were calculated as 5, 1, 2.9 and 30, respectively. The results of this optimization in the studied process show that the duration of the planned maintenance should be increased compared to the existing program, and this can be due to compensatory maintenance when the false alarm is out of control of the process.

The high prevalence of cardiovascular diseases has caused many health problems in countries. Cardiac Rehabilitation Programs (CRPs) is a complementary therapy for Percutaneous Coronary Intervention (PCI) patients. However, PCI patients hardly attend CRPs. This study aims to decipher the reasons why PCI patients rarely participate in CRPs after PCI. The parameters affecting the attendance of the patients at CRPs were identified by using the previous studies and opinions of experts. A questionnaire was designed based on the identified parameters and distributed among PCI patients who were referred to Tehran Heart Center Hospital. According to data mining approach, 184 samples were collected and classified with three algorithms (Decision Trees, k-Nearest Neighbor (kNN), and Naïve Bayes). The obtained results by decision trees were superior with the average accuracy of 82%, while kNN and Naïve Bayes obtained 81.2% and 78%, respectively. Results showed that lack of physician’s advice was the most significant reason for non-participation of PCI patients in CRPs (P< .0001). Other factors were family and friends’ encouragement, paying expenses by insurance, awareness of the benefits of the CRPs, and comorbidity, respectively. Results of the best model can enhance the quality of services, promote health and prevent additional costs for patients.

In the competitive market of perishable cargoes, determining the price of the product and making opportunities for customers to accelerate the sale of goods through discounts is crucial. Over the life of perishable goods, generally its value reduced to the customer, in this situation, to encourage the purchase, policies such as a discount or reduced price sales policies can be effective. Literature has not provided a model for determining the optimal time to announce a price reduction. While early or late prices announcement could reduce profit, the aim of this paper is to analyze such a model at the level of an enterprise. In the modeling, we assumed that by announcing price discount, tangible changes occur in demand, and demand is a function of price and time. The demand rate in the discount time is decreasing in the beginning of the time and then declining over time. The purpose of the model is determining the optimal price, discount time and order size to maximize the total profit in a single period. After modeling, concavity of the profit function is considered and optimal pricing and discounts are exclusive. Then, a heuristic algorithm derived from the literature was used in order to determine the optimal price, the optimal discount time and the optimal order quantity.

Introduction In this article, the term "perishable" is used for goods that, due to rapid technological changes or the introduction of new products by competitors, should lose their value over a period of time. For example, fashion goods in the season will quickly fall in price, because otherwise the need for spare parts for military aircraft is one of fashion goods that would be unusable if a new aircraft model is being used (Khanlarzadeh et al., 2014). When non-perishable products approach their expiration date, they often use price discounts. Tajbakhsh et al (2011) developed an inventory model at a price of Random Discount, and numerical analysis that showed cost saving through discounts. The research conducted in the field of pricing and bidding for the aforementioned commodities, only several models have been developed that are either definitive or random models with known distributions (Wang, 2012). Rajan et al. (1992) have developed pricing policies and ordered for definitive applications. Also, if problem modeling occurs in the supply chain, competition between the members of the chain is formed to generate more profit. Zhang et al. (2015) considered a supply chain model with a producer and retailer for degraded items at a time-rate and price-dependent demand. They have designed an algorithm for obtaining price and investment protection technology strategies, and have examined both centralized and decentralized scenarios. In this article, the pricing of a perishable goods is considered under discounted conditions, and given the importance of selling these products over the life of the customer, it is essential to pursue a policy that can encourage customers to buy more. Also, the discount policy comes with the synchronization of the demand function during the discount period. In the absence of discounts, the demand rate is a function of the time and price, and in the discount period, the demand function is initially at an incremental time, and after the discount, the time is reduced. In the literature examined, the price for the final customer, which affects demand and does not change the demand for demand function, is not taken into account. For example, Meihami and Karimi (2014) show a change in demand after advertising with a coefficient in the demand function has given. While in the real world, with the announcement of a discount, the function of the rate of demand for perishable goods varies and is not mentioned in any of the previous investigations. In the following, we describe the assumptions and symbolization of problem modeling. Materials and Methods It is assumed that the maximum inventory in the first period (I0 ) is the order quantity, and its decreasing is only affected by demand. As a price mark-down should always be applied before the expiration date of the product, the time horizon for product selling can be divided into two intervals: [0, t] and [t,T].
Notice that due to the discount after the price mark-down, the demand rate function during the time intervals [0, t] and [t, T] is different, in the interval [t, T], the product is sold out at the discount price p(1-a). Due to the discount, a moderate growth in the demand initially occurs; however, it reduces gradually (see Fig. 1.).
There is no shortage, nor surplus in the end of the time horizon, i.e., period T, so the inventory level is the demand in that period. On the other hand, the demand in the time interval [0,t] can be expressed as follows and the profit can be expressed, The methodology must be clearly stated and described in sufficient detail or with sufficient references containing the research model and tools. Discount time (t) The proposed algorithm is used for solving the following numerical example to illustrate the solution process and results. Mathematica 9 was used in this regard.
Example.The following parameters and functions are used.
T=2, c=200, =0.3
Table 1 show, the convergence of the algorithm, where for the quasi-optimal tolerance e, it results in p*= , t*=1.008, TP*= , Q*= , and the numerical results are obtained for the price interval [400, 1000].
Table 1- Computational results of Example 1. In this paper, the pricing model for non-perishable goods was presented under discounted sales terms. In modeling the hypothesis problem by declaring a decline in sales prices, the demand rate has a tangible change, and demand is a function of price and time. In this paper, it was proved that the goal of profit is optimal and unique in terms of optimal price and discount time. With using a simple algorithm, a numerical example of a model and results are analyzed using sensitivity analysis on model parameters. The model presented in this paper is a comprehensive and complete model, and compares to different values of the parameters of the flexible demand function. The model presented in this study can be expanded in several ways; the demand rate in this paper is definite. It is considered to be time-dependent, with its probability, it is possible to define a suitable topic for future research. We can also consider the discount percentage variable. On the other hand, advertising policies, delay in payments and coordination models in the supply chain system and reviewing the results can be considered.

Gate scheduling is a key activity at airports that is proposed as an optimization problem. The main purpose of this problem is to find an assignment for the flights arriving and departing while satisfying a set of practical constraints. Studies show that the gate assignment tables have been used to minimize the gate flights delay and maximize the gate efficiency and productivity. Depending on the situation, different objectives become important. If the load balancing with number of passengers in the gates becomes a bottleneck one has to make sure that the flights are equally spread over the different gates. This load balancing objective function has to be balanced with other objectives, especially minimization total delay time and maximization of the total gate assignment preference score. The related problem is formulated as a mixed-integer programming (MIP). We address this problem using real life data from Mehrabad International Airport for both small and medium size problem. To find the set of Pareto solutions, NSGA-II algorithm is proposed to demonstrate the effectiveness of the solutions which is obtained in small dimensions compared with the results obtained by the method of epsilon constraint. The results show that the percentage of error of objective function compared to epsilon constraint method is less than 1.5% for all problems. Indeed, this shows the efficiency of proposed algorithm which is recommended for solving the medium and large size problem.

Optimizing gate scheduling at airports is an old, but also a broad problem. The main purpose of this problem is to find an assignment for the flights arriving at and departing from an airport, while satisfying a set of constraints.A closer look at the literature in this research line shows thatin almost all studies airport gate processing time has been considered as a fix parameter. In this research, however, we investigate a more realistic situation in which airport gate processing time is a controllable. It is also assumed that the possible compression/expansion processing time of a flight can be continuously controlled, i.e. it can be any number in a given interval.Doing sohas some positive effectswhich lead to increasing the total performance at airports’ terminals. Depending on the situation, different objectives become important.. Therefore, a model which simultaneously (1) minimize the total cost of tardiness, earliness, delay andthe compression as well as the expansion costs of job processing time, and (2) minimize passengers overcrowding on gate is presented. In this study, we first propose a mixed-integer programming model for the formulated problem. Due to complexity of problem, two multi-objective meta-heuristic algorithms, i.e. multi-objective harmony search algorithm (MOHSA) and non-dominated sorting genetic algorithm II (NSGA-II) are applied in order to generate Pareto solutions. For calibrating the parameter of the algorithms, Taguchi method is used and three optimal levels of the algorithm’s performance are selected. The algorithms are tested with real-life data from Mehrabad International Airport for nine medium size test problems. The experimental results show that NSGA-II has better convergence near the true Pareto-optimal front as compared to MOHSA; however, MOHSA finds a better spread in the entire Pareto-optimal region.Finally, it is possible to apply some practical constraints into the model and also test them with even large real-life problems instances.

Determining appropriate inventory control policies and product price are important aspects in the competitive markets of perishable products. Customers’ willing to pay for perishable product is declining when approaching to the end of product’s expiry date. In this paper, we consider price discount in pricing model as an alternative approach to influence on consumers’ purchase decision. The model determines the optimal values of selling price, discount time and replenishment schedule simultaneously such that the total profit is maximized. However, because of demand increase during the discount interval, different demand rate function which is a function of price and time is used in the model. In this regard, at first, we model the problem without regarding discount that its solution shows an impossible result in reality which the replenishment time is very short. But then with regarding discount in the model, more products are sold and thus the profit increases. Finally, we solve two numerical examples used an iterative algorithm by performing a sensitivity analysis of the model parameters and also discuss about specific managerial insights.

In the real world, risk and uncertainty are two natural properties in the implementation of Mega projects. Most projects fail to achieve the pre-determined objectives due to uncertainty. A linear integer programming optimization model was used in this work to solve a problem in order to choose the most appropriate risk responses for the project risks. A mathematical model, in which work structure breakdown, risk occurrences, risk reduction measures, and their effects are clearly related to each other, is proposed to evaluate and select the project risk responses. The model aims at optimization of defined criteria (objectives) of the project. Unlike similar previous studies, in this study, the relationship between risk responses during implementation has been considered. The model is capable of considering and optimizing different criteria in the objective function depending on the kind of project. In addition, a case study related to petroleum projects is presented, and the corresponding figures are analyzed.

Operational failures in centrifuge pumps could be hydraulic or mechanical. However, most of these mechanical and hydraulic failures are connected cause of their operational nature and finding the right cause is due to considering numerous mechanical and hydraulic signs and parameters in pumps. On the other hand, due to non-linear and fluctuant behavior of pumps in the matter of time and not precise and clear data from a complicated system such as a petrochemical unit installations, investigating the failure possibilities in pumps by exact mathematical equations is so hard. However, the expert staff in maintenance could find the cause of failure by getting benefit of imprecise and verbal rules of "if-then" and the awareness of the non-clearance in system. However, it should be noted that this process takes time and also it is so dependent on the knowledge of expert staff, also human error can cause wrong decision-making and it declines reliability in the system. Therefore, this study is looking forward to find a collection of imprecise and verbal rules by using the reference book of "OREDA", also the pump handbook and the knowledge of expert staff in maintenance. With the acquisition of knowledge and Extraction of linguistic rules from taking effect between critical failure modes of mechanical and hydraulic parameters of process pump is created the relationship between these parameters and verbal rules, also by using a neural network of MLP category for the cases to train the neural network. Obtained results in companion with the average on accuracy, precision and recall parameters would be the approval of our method.

Optimization of Airports, gate scheduling is a vital activity. The main purpose of this optimization is to find a proper allocation for the flights arriving and departing by considering all of limitations. Studies show that the gate scheduling is applied for minimizing the gate flights delay and maximizing the gate efficiency and productivity. The optimization is formulated as a mixed-integer programming (MIP). The paper is studied data from Mehrabad International Airport. Our results show that the model can be solved by using NSGA-II algorithm in a short time. The set of Pareto solutions are ranked by TOPSIS method and the first 10 solutions are reported. The results show that although adding the first objective function (crowd congestion) leads to %8 reduction of the third objective function (the total gate assignment preference); the first objective function has a positive effect on the satisfaction of passengers.

In the organizational studies, the measurement of organizational learning capabilities has become an increasingly important area. There are several models in literature that have been generated by statistical data from manufacturing firms. In this paper we have used a structural equation model for measurement of organizational learning in hospitals as services firms. In our model, there are four dimensions for organizational learning measuring: managerial commitment, systems perspective, openness and experimentation, and knowledge transfer and integration. The results imply that organizational learning is measurable by these four dimensions. The model could be use to improve learning capability by managers. However, the average of knowledge transfer and integration capability and managerial commitment capability is the highest and the lowest averages respectively. Comparison of our results with previous studies implies that being the service firm as a human-based organization lead to improvement of system perspective and knowledge transfer and integration capabilities.