محمدصابر فلاح نژاد

Generally, selecting an investment portfolio with appropriate returns that is also secure and auditable has been one of the issues raised in recent decades. For this purpose, the present research proposes an appropriate approach using ideal and anti-ideal values, ideal values, as well as maximum deviations of each objective, considering the sample in the examined market, fuzzy goals, interval fuzzy values for each asset, and their combination with satisfaction functions, fuzzy ideal planning, and weighting objectives using expert decision-makers' opinions, as well as the development of fuzzy basic weighting method. It seeks to select an investment portfolio in the digital currency market.

In this research, a new approach to selecting an investment portfolio based on uncertain data and multi-objective uncertain planning is proposed, and ultimately, the proposed approach is implemented in the digital currency market for portfolio selection.

The results of the present study show that the proposed model of investment portfolio compared to the base model not only led to higher returns but also had higher audibility and better risk control. In other words, the proposed model outperformed the base model in all the objectives under study.

Originality/Value:

 As distinguishing features of the proposed model of this research, one can mention: 1) constructing and using fuzzy distribution functions and calculating ideal values and expected ranges for all desired objectives considering the conditions of the examined market research using simple mathematical modeling, 2) utilizing the experience of financial market experts in planning model for selecting suitable investment portfolios in emerging financial markets, 3) presenting an approach to calculating portfolio risk in conditions of information scarcity in the problem environment using fuzzy theory, 4) development of the fuzzy benchmark-criterion method for weighting the objectives under study in the problem considering the expertise of financial market experts, and 5) simple modeling, considering interval fuzzy values in the model, and being usable for all individuals with different levels of investment knowledge.

The Permasin engine is a critical mission-oriented system, the failure of which will cause the failure of the main mission. Comprehensive studies on its reliability can be a step towards improving the performance of this system. The aim of the article is to analyze the reliability of the Permasin engine in the specified scenarios. In this article, first of all, the structure of Permasin engine as the studied system is described and the breakdown structure of the product is drawn for this system, and according to the mission-oriented nature of this system, there are 2 time scenarios, the basis of floating performance, definition and failure rate for sensitive parts from the standard. MilHDB-217 and NPRD-95 will be calculated in two optimistic and pessimistic modes. By using the breakdown structure, the connection of specific system components and the reliability block diagram are drawn in the Reliability Workbench software. Finally, the reliability of the subsystems and the studied system is calculated separately for both working scenarios. The results show that drive and motor subsystem has the lowest level of reliability compared to other subsystems in rated power.

The idea that any deviation should be recognized as soon as possible will often be impractical. Despite the existence of numerous assignable causes in the process, their eects may be so small and minor against the permissible tolerance. Identifying them seems uneconomical from practical sights. If the process reaches a high level of capability, the production may be acceptable even though assignable causes befall. Since customer expectation will not be aected in this case, it is not economical to stop the process. By considering the level of speci- cations, some changes in the average can be allowed. Dividing the conditions of the monitored process into just black and white can be simplistic. In such cases, traditional control charts with two zones are not applicable. By dening the zone of indierence, permissible deviations can be tolerated. For such a situation, Acceptance Control Chart (ACC) is developed based on three zones. Suppose that a statistically assignable cause is detected using the traditional control charts; however, no signal is observed by the ACC. Thus, this change does not result in a nonconforming output, and there is no need to stop production since no operational loss occurs. The most important assumptions of the ACC are the normality and independence of the monitored data. In some industrial/non-industrial processes (e.g., continuous production processes, nancial processes, network monitoring, and environmental phenomena), serial correlation can be extracted among samples which violates the assumption of independence. Autocorrelation reduces the performance of traditional control charts by producing frequent false signals in the in-control state or makes them respond slowly to the detection of the outof- control state. The main purpose of this study is to develop an ACC for monitoring the data of the most widely used autocorrelated process, namely the rst-order autoregressive process AR(1). In this regard, two types of ACC are extended for the residuals of AR(1) processes. Upon evaluating the performance of monitoring methods using the average run length (ARL), it is found that the proposed EWMA chart has better results. Moreover, the economic-statistical design of the proposed chart is carried out at a lower cost.

In recent years, supplier selection is one of the vital issues in supply chain. In the past, supplier selection was only based on costs. Years after that, further than costs, factors such as quality, minimum delivery time, etc. have become important. So, it has been shown that sustainable supplier selection concerns environmental and social factors besides the economic factors that have to be considered simultaneously. Hence, supplier selection is a multiple criteria problem in which qualitative and quantitative factors must be considered. One of the causes of environmental criteria importance is the pollution which is increasing by the activities of companies. Also decreasing the available resources is another cause of such. Finally, to create a sustainable supply chain, sustainable supplier selection is very important. In this paper, a sustainable supplier selection is considered. A method is presented for the first time to evaluate suppliers with an Evidential Reasoning (ER) approach which considers the uncertainties of personal judgments. Also, in conditions that there is an absence of information in some of the sub-criteria during the comparison of suppliers, they can be compared based on the minimum and maximum utility function of the suppliers' value. At first, criteria and sub-criteria are chosen in order to evaluate and select the suppliers in sustainable supply chain based on company strategies, expertise and literature review in this field. Then, using the BMW, an effective multiple criteria decision-making method, weights of criteria and sub-criteria determined and in the end to evaluate and rank the suppliers an ER method is employed. ER approach is an algorithm based on a multi-criteria evaluation matrix and combination of forecasts Dempster---Shafer and by using that, factors of multi-level structures can be combined. Imperfect evaluation resulted from the lack of information or the inability of the assessor in performing precise judgments or the assessor's error in group decision making, is considered via the error degree of the combined information and utility intervals to determine the imperfect degree of the primary information in decision analysis are provided. In the end, a case study is provided to investigate the procedure in details.

Accidents as a threat factor to the transport system have widespread political, social, and economic dimensions, which is increasing in developing countries. Iran, as a developing country, has not escaped this danger, but in recent years it has taken preventive measures and crash statistics has been decreasing. Crash injury severity is one of the most important criterions of measuring the costs of accidents. Different methods have been used for predict modeling. Support Vector Machine is a relatively new modeling technique which was proposed to solve the classification and regression problems. That shows accurate and acceptable performance. In the present study, it has been tried to model the severity of accidents with a combination clustering and classification approach, with the help of neural network algorithms, simple parsing, SVM, KNN, and C4.5 algorithms and by comparing the algorithms used assess the ability of each of the algorithms in the prediction of the severity of accidents. The purpose of this study is to evaluate the performance of support vector machine algorithm to predict the severity of road accidents and identify the factors that affect the severity of accidents.

Preventive maintenance scheduling of generating units is addressed as a crucial issue in power system studies due to its severe impacts on power systems' asset man-agement by reducing operation cost while enhancing re-liability worth. In this paper, we describe an application of statistical analysis for determining the best preventive maintenance strategy in the case of parallel, series, and single-item replacement systems. A key aspect of indus- trial maintenance is the trade-o between cost and time of performing preventive maintenance operations. This article deals with two main issues related to the preven- tive maintenance in order to minimize the cost per unit time: (1) specifying the best time for performing preven- tive maintenance actions in parallel, series, and single- item replacement systems; (2) determining the required number of spare parts and facilities. in single-item replacement and parallel systems, respec- tively. In this proposed maintenance strategy, preventive maintenance operations are regularly performed on the production unit in equal time intervals and maintenance actions return the facilities to a good-as-new condition. In the proposed model, the number of failures for a spec- i ed facility follows the Poisson distribution, and failure rate of the Poisson distribution follows Gamma process. In addition, equipment' failure being earlier than the de- termined starting time for the preventive maintenance operations would impose too much cost on each system. Therefore, to consider this constraint, it is assumed that there is a linear relation between recovering cost from unplanned failures and time to failure. Moreover, all costs related to maintenance are supposed to be known and the cost of a preventive repair is appreciably less than that of a failure and its associated repair. Finally, three examples are presented to demonstrate the e ec- tiveness of the proposed models for each system. We use MATLAB software to obtain the optimal value of parameters in cost models in the proposed approach. To nd the optimal value of decision variables in each system, a search procedure is applied.

This paper studies a series production system through the integration of the decisions associated with Maintenance Management (MM) and Statistical Process Control (SPC). Hence, the primary question of the paper can be stated as follows: In a series production system, how can the decisions of MM and SPC be coordinated? To this end, an integrated mathematical model of MM and SPC is developed. Using a method of factorial design, sensitivity analyses are performed. According to a stand-alone maintenance model, the effectiveness of the integrated model is assessed. The series production system investigated consists of identical units. Each unit has two operational states including an in-control state and an out-of-control state. The system is in-control if both units of the system operate in the in-control state. On the other hand, the system is out-of-control, if at least one of the units operates in the out-of-control state. The failure mechanism of each unit is based on a random variable with a continuous distribution. The results of analyses clarify that the integrated model improves the profit of the system.

Since the demand in air transport system has the most influence on increasing prosperity and efficiency of this system, identifying the factors that attracts the passengers to air transport is essential. This topic has got an importance in developing countries in recent years because of the slow growth rate of number of domestic flight passengers. In this research which surveys the effective factors on demand of domestic air transport, for gathering required information from passengers, a questionnaire was designed including 20 effective parameters on air transport demand based on consulting experts, university professors and past research studies. It was asked from the passengers to rank the parameters according to their importance. These parameters were categorized using “Factor Analysis” with 6 factors of “cost”, “services”, “time”, “application of up-to-date technology”, “satisfactory and secondary services” and “safety” respectively. Obtained factors were 67.7% effective on changing passenger demands of domestic air transport. The factor “cost” has had the greatest impact with 20.4 %. “Structural Equation Modeling” has been used for checking the “Factor Analysis” results. Modeling results proved the correctness of factor analysis. Furthermore, the modeling has showed that the most mutual effectiveness has been between the factors “cost” and “services” with the value of 0.18. The results of this research express practical implications for airport Companies and airlines in the field of programming air transport, increasing demand attraction of passengers and eventually improvement of economic conditions at a national level.

Accuracy in estimating the needed effort for software development caused software effort estimation to be a challenging issue. Beside estimation of total effort, determining the effort elapsed in each software development step is very important because any mistakes in enterprise resource planning can lead to project failure. In this paper, a Bayesian belief network was proposed based on effective components and software development process. In this model, the feedback loops are considered between development steps provided that the return rates are different for each project. Different return rates help us determine the percentages of the elapsed effort in each software development step, distinctively. Moreover, the error measurement resulted from optimized effort estimation and the optimal coefficients to modify the model are sought. The results of the comparison between the proposed model and other models showed that the model has the capability to highly accurately estimate the total effort (with the marginal error of about 0.114) and to estimate the effort elapsed in each software development step.

Injury severity is an important index to analyse cost of crashes. Several approaches have been used to model and predict the crash severity. In this study, using road traffic accidents in seven provinces of Iran (Isfahan, Khuzestan, southern Khorasan, Qom, Qazvin, Kerman and Mazandaran), and Binaary Logit model has been used to predict the fatal or injury crashes. The effect of important variables on the crash severity of each of the three types of accidents involving motorcycles, sedans and trucks was investigated. Also, factors such as increasing the difference in weight of vehicles, deviations to the left, increasing the age of drivers, pedestrian presence and exceeding speed limits lead to increased crash severity and fatal accidents.

Although most companies spend less on product design, experience shows that, these companies have to pay higher costs due to production problems or loss of market. Literature studies show that the Design for Six Sigma is a powerful approach for designing products, processes and services. While the tools used in Six Sigma require a process to be in place and functioning, DFSS has the objective of determining the needs of customers and the business, and driving those needs into the product solution so created. DFSS is relevant to the complex system/product synthesis phase, especially in the context of unprecedented system development The aim of this project is to provide a global method for designing robust products based on the Design for Six Sigma methodology. The methodology integrates three concepts: reliability-based optimization, robust design and multi-objective optimization.The methodology proposed for the design of Six Sigma can be explained in four stages: formulation, optimization, simulation and selection. The algorithm is to generate several Pareto-optimal solutions at the optimization stage. The algorithm was applied to the design of lightweight concrete blocks, with consideration of customer need, in three main areas: weight blocks, cost blocks and strength blocks. First, considering expert preferences, the mathematical modeling of the blocks was determined. Second, interactive multi-objective algorithms, taking the decision maker's preferences into account, were developed to generate twelve Pareto-optimal solutions that maintain a probability of constraint satisfaction. Then, 1 solution optimization (per cubic meter of: 409 kg of cement, 1.4 kg of Polypropylene fibers, 12.14 kg of silica and 8.8l of foam) was adopted for implementation as a compromise between the three criteria (the savings compared to the baseline solution, the coefficient of variance (robustness), and the degrees of desirability). The results show that the variable Polypropylene fibers cause the most variations in cost functions, while Polypropylene fibers, silica, water and foam are the most critical variables for the constraint. Blocks were built and compressive strength was obtained that was consistent with the calculated result.

Manufacturers have found the great role of suppliers in achieving competitive advantages. In recent years, satisfaction of suppliers in supply chain has been considered in some researches. In fact, it is told that manufacturers and suppliers should cooperate in their activities and become each other’s trusted partners. This paper seeks to find the factors influencing a suppliers’ satisfaction. The goal is achieved by reviewing the existing literature and then designing the proper questionnaire for Iranian food industry. The questionnaires are analyzed using PLS approach. The results show that the factors trust, communication and payment policies directly influence the satisfaction of a supplier and the factors conflict management and purchasing policies have indirect influence on supplier satisfaction.

A simulation-optimization approach is proposed for replenishment planning and shelf space allocation. The customers’ demand is divided into fixed and variable demand. Each customer follows a given path while shopping in the store. By dividing the store space into several zones and calculating the related substantial and random utilities، an analytical equation is proposed for the probability of zone visits. Due to the complexity of the proposed equation، a simulation method is used to evaluate the customers’ movements and predict the variable demand. A profit-based integer-programming model is then formulated for the case problem that needs the output demand of the simulation phase. However، the optimal values of some decision variables should be available through simulation. Therefore، a simulation-optimization algorithm is iteratively run since a pre-determined small deviation from the expected profit goal is achieved. Finally، the numerical results are reported for a small-sized problem.

Reverse logistic has attracted a lot of attention from researchers in recent years due to government regulations، environmental problems، extension of social responsibility and customer demands. In addition، the decline in the natural resources and raw materials combined with the increase in production costs and problems of dealing with trash of the industry and consumer products makes the cycle of consumption very interesting to researchers from the production point to the last stage of recycling. This subject gave way to newer concepts like integrated، closed-loop and stable supply chain in the past decade. This paper presents a robust design for a multi-product، multi-echelon، closed-loop logistic network model in an uncertain environment. To this aim، a multi-objective mathematical programming model is developed wherein its objective functions include profit، social and environmental impacts. First، a deterministic mixed-integer linear programming model is developed for designing a closed-loop supply chain network. Then، the robust counterpart of the proposed mixed-integer linear programming model is presented by using the recent extensions in robust optimization theory. Finally، to assess the robustness of the solutions obtained by the novel robust optimization model، they are compared to those generated by the deterministic mixed-integer linear programming model in a number of realizations under different test problems.

In each organization, management pursues implementing systems for attaining his objectives until provides suitable environment for presenting services. Call centers are one of the service centers that have been investigated in recent years. The development of call center industry resulted in complicating these systems that has leaded to complicated management and design of these systems. The objective of this paper is the evaluation of call center systems. For this objective, first with the understanding most important problems in call center units, the simulation model of this system is designed and then validity of this model for adapting it with real system is analyzed. At the end, some solutions are presented for improving the performance of system by using design of experiments. The proposed scenarios are simulated and improved model is introduced.

In this paper, we consider a supply chain consisting of one producer and multiple retailers, where the producer 165 applies a vendor managed inventory in the supply chain. Production of a single product is assumed and the demand for this item in the retail market is a decreasing function, with respect to price. Although similar problems have been studied and analyzed by several researchers in the past, this work diers from others in several ways. The most important contributions of this article are: (1) Modeling centralized and decentralized states of the considered supply chain as non-linear programming. (2) Considering two situations for the decentralized supply chain: (a) producer sells the product at the same unit price to all retailers; (b) producer sells the product at dierent prices to retailers; (c) producing random data for parameters of the models and comparing centralized and decentralized state performances with each other; and (d) providing a sensitivity analysis for model parameters and vendor managed inventory systems. It is worthwhile to note that the decentralized state formulation is performed based on the Stackelberg game theory, and under the assumption that the producer is the leader of the game. The results of our analysis indicate that; (i) dierences in selling prices for retailers does not have much eect on the member prots of the supply chain, but can have a signicant eect on prices; (2) sensitivity analysis of the model parameters indicates that the in uence of each parameter on system performance signicantly depends on whether the overall demand of the system is less than the production rate or is equal to the production rate; (3) considering system performance in the centralized state as a benchmark, system prot in a decentralized state is, on average, 0.94 centralized system prot. Also, for cases in which the overall demand of the system is less than the production rate, the dierence between centralized and decentralized states is greater than that of the case whose production rate is equal to overall demand.

Consider a supply chain that consists of one vendor and multiple retailers. We assume that the vendor procures product from an external source and sells it with the same wholesale price to the retailers. Demands in retailers’market are decreasing function of the price and vendor makes use a vendor managed inventory strategy. In this paper we propose model of supply chain in centralized and decentralized state. Supply chain performance in centralized state can be analyzed by mathematic optimization model while for analyzing supply chain performance in decentralized state use Stackelberg game. Finally, numerical analyses about the proposed models are done and performance of supply chain in centralized and decentralized state is compared.

A heuristic method based on simulation and design of experiments for performance improvement of assembly line is presented in this paper. In the proposed method, all effective factors on the performance of an assembly line are specified using the expert's point of view and then a 2k factorial design is used for the selection of the most effective factors. Also a factorial design is applied for assessment of interaction among important factors and comparison of different levels. A simulation method is employed for evaluating the performance of proposed alternatives instead of using real case. A straightforward assembly line analysis is presented and exemplified in this work by extracting and analyzing effective factors of an auto light company. Number of workstations, operators and speed of machines are chosen as the main factors. Next to the identification of different levels using factorial design, the method showed significant improvement on the assembly line of auto light company.