فهرست مطالب masoud seidi

The correlation of different samples can be described by analytical models such as random matrix theory. In this study, we tried to describe the correlation of different types of ultraviolet values in different months, weeks, and hours to get a significant relationship of special times, which one needs to get enough intensity of the sun or avoid getting sunburn.

To this aim, we focused on the hourly and daily mean amounts of ultraviolet A, B, and C intensities of solar radiation in Tabriz urban area were measured during a full year of 2017-2018. We used such ultraviolet values which are measured at the same hour of the day to satisfy the same symmetry criteria which are necessary in random matrix theory. These data are unfolded and classified in different sequences to analyze in the nearest neighbor spacing distribution framework via the maximum likelihood estimation technique.

Strong correlation is yielded for daily values of UVA in comparison with the other types of ultraviolet radiations. Also, we considered the dependence of correlation degrees of these three types of ultraviolet to average temperature and humidity at different months.

The results propose more correlation of UVA indices in August while such correlation of UVC radiations are yielded in December.

One of the industrial parts that requires very high manufacturing accuracy is industrial molds and especially cutting molds. In these molds, the clearance of the dies is equal to 0.1 of the thickness of the sheet, so the accuracy of making these molds is very important. Today, the wirecut process is widely used in making these molds. In the process, due to the lack of contact between the tool and the work piece, there is no mechanical tension and the produced parts have high precision. Nevertheless, in order to achieve the high precision required in the production of cutting molds, various methods are used. In this research, using the response surface method, the dimensional accuracy value has been investigated based on three parameters of wire speed, wire tension and generator power for Mo40 steel workpiece. Based on this method, at first, the importance of each parameter on dimensional accuracy was determined. Then, by deriving the equation according to the conducted tests, the optimal value of dimensional accuracy was extracted based on the mentioned parameters. The results showed that for tension values of 1.3485 kg, wire speed of 10 cm/s and power of 46.7677%, the accuracy value reaches its maximum value. Finally, these values were experimentally tested and a 0.2% error was recorded. Therefore, by using the method of the response procedure, the amount of dimensional accuracy can be used in the wirecut process of industrial steel molds.

Pressing molds are widely used in the industry due to the high speed of parts production. Due to the very low clearance between the mandrel and the matrix and having complex shapes, the production of these molds is very expensive and costly.  The hardness of the mold and subsequently their fatigue life should be high. One of the processes that has the ability to create surfaces with high dimensional accuracy and complex shapes is the wirecut process. In this research, in order to improve the performance and increase the life of cutting dies, the hardness of Mo40 steel is optimized. For this purpose, based on the method of the response procedure, the design of the experiment has been designed for the three parameters of wire feed speed, wire tension and generator power. Next, the obtained data are clustered and then fuzzy rules with three inputs (wire speed, tension and power) and output (hardness) are extracted. The obtained rules were entered in the toolbox of fuzzy inference systems of MATLAB software. Based on the defined fuzzy inference system, it is possible to predict the hardness based on the parameters of wire speed, wire tension and generator power. In the next phase, based on this system and within the range of available variables, the optimal value of hardness and corresponding variables were extracted. In the final phase, these values ​​were experimentally tested and their agreement with the obtained value was observed.

In this study, the statistical correlation of the electric quadrupole transition probabilities in the spherical nuclei is investigated. To this aim, the spherical even-even nuclei in the 100 < A < 126 mass region are selected and the electric quadrupole transition rates of different levels in the ground band are determined by the interacting boson model in the U(5) dynamical limit. A non-parametric kernel density estimation method is used in the framework of nearest neighbor spacing distribution of random matrix theory to consider the statistical correlation of these quadrupole transition rates. Also, the Kullback-Leibler divergence is used to describe the regular or chaotic behavior of the considered sequences. The results show the correlation of the electric quadrupole transition probabilities between different levels of the ground band. Also, the correlation increased for such transitions that the angular momentum of the initial state of quadrupole transitions increased.

Nowadays, supply chain management (SCM) is an interesting problem that has attracted the attention of many researchers. Transportation network design is one of the most important fields of SCM. In this paper, a logistics network design is considered to optimize the total cost and increase the network stability and resiliency. First, a mixed integer nonlinear programming model (MINLP) is formulated to minimize the transportation time and transportation cost of products. The proposed model consists of two main stages. One is a normal stage that minimizes the transportation and holding costs, all manufacturers are also assumed to be healthy and in service. In this stage, the quantity of customer demand met by each manufacturer is eventually determined. The second is the resilience stage. A method is presented by creating an information network in this supply chain for achieving the resilient and sustainable production and distribution chain that, if some manufacturers break down or stop production, Using the Restarting and load sharing scenarios in the reactive approach to increase resilience with accepting the costs associated with it in the supply network and return to the original state in the shortest possible time, the consequences of accidental failure and shutdown of production units are managed. Two capacities are also provided for each manufacturer Normal capacity to meet the producer's own demand Load sharing capacity, Determine the empty capacity and increase the capacity of alternative units to meet the out-of-service units demand In order to solve the model, we used GAMS & Matlab software to find the optimal solutions. A hybrid priority-based Non-dominated Sorting Genetic Algorithms (NSGA-II) and Sub-population Genetic Algorithm (SPGA- II) is provided in two phases to find the optimal solutions. The solutions are represented with a priority matrix and an Allocated vector. To compare the efficiency of two algorithms several criteria are used such as NPS, CS and HV. Several Sample problems are generated and solved that show the Sub-population Genetic Algorithm (SPGA- II) can find good solutions in a reasonable time limit.

In this research, we have considered quantum phase transition for even-even neodymium isotopes ( ) using the Hamiltonian of Interacting Boson Model (IBM-1) in the framework of affine SU(1,1) Lie algebra. The energy spectrum of this chain has obtained by calculating the Hamiltonian control parameters with Least Squares method. In the following, energy surfaces using coherent state formalism has calculated. Changes observed in the energy surfaces and the values of showed that the  isotope is the transitional nuclei between U(5) and SO(6) limits. The results of this model are in good agreement with New Empirical Formula (NEF).

One of the most important fields of logistic network is transportation network design that has an important effect on strategic decisions in supply chain management. It has recently attracted the attention of many researchers. In this paper, a multi-stage and multi-product logistic network design is considered.This paper presents a hybrid approach based on simulation and optimization (Simulation based optimization), the model is formulated and presented in three stages.  At first, the practical production capacity of each product is calculated using the Overall Equipment Effectiveness (OEE) index, in the second stage, the optimization of loading schedules is simulated. The layout of the loading equipment, the number of equipment per line, the time of each step of the loading process, the resources used by each equipment were simulated, and the output of the model determines the maximum number of loaded vehicles in each period. Finally, a multi-objective model is presented to optimize the transportation time and cost of products. A mixed integer nonlinear programming (MINLP) model is formulated in such a way as to minimize transportation costs and maximize the use of time on the planning horizon. We have used Arena simulation software to solve the second stage of the problem, the results of which will be explained. It is also used GAMS software to solve the final stage of the model and optimize the transporting cost and find the optimal solutions. Several test problems were generated and it showed that the proposed algorithm could find good solutions in reasonable time spans.

The performance-based budgeting (PBB) allocates budget to outcomes. This research, with the introduction of productivity as an alternative to the outcomes, presents a mathematical model for performance-based budgeting in order to allocate budget to productivity criteria. New trends in budgeting are process-oriented, so the productivity is suitable for PBB. This research presents a mathematical model for PBB. The model has been designed by Chebyshev's goal programming technique. Data for calculating productivity indicators were collected from gas refineries of Iran in 2011–2015 and analyzed by Excel and GAMS software. Then, the model was tested for determining the 2016 budget of those refineries. The model was solved by LINGO software by linking it to Excel. The solution of the model reduced 1.47% of the total refinery's budget compared with the actual budgets for 2016. The results of this study showed that the presented model provides significant improvement in the level of achievement of goals and the objective function. Saving costs and collecting funds from low-productivity units and directing them to high productivity is a strategic and important policy.

Supply chain management in healthcare sector is of utmost importance due to its effect on individuals’ health status compared to other industries. In the current world economic situation wherein logical thinking should be based on lifetime costs of products ,as well as supply chain sources and processes, it is essential to have an agile supply chain to have a socio-environmental performance creating competitive advantage.
 

This study was a survey with a correlational design considering its methodology and purpose. The statistical population of this study included the staff of public hospitals in Ilam province, Iran; of which, 340 individuals were selected as the participants based on Krejcie and Morgan’s sample size determination table. Moreover, the SPSS Statistics Software and LISREL Software were used to analyze the data in this study.
 

The statistic of the Kaiser-Mayer-Olkin (KMO) index was equal to 0.844 implying sampling adequacy. Moreover, all the factors affecting supply chain agility had a normal distribution and the test statistic was larger than 1.96 for all the factors, suggesting their relationship with supply chain agility. The positive correlation between supply chain agility and competitive advantage was further confirmed based on the research findings.Additionally,the value of the goodness of fit index (GFI=0.96) showed the fit of the model and the test statistic of the model (T=9.60) revealed the significant impact of supply chain agility on creating the competitive advantage.
 

The results of the present study demonstrated that the seven dimensions of computer-based technologies, flexibility, relationships with suppliers, use of modern technologies, collaborative partnerships, sensitivity to market, and responsiveness of demands had effects on supply chain agility in hospitals. Moreover, public hospitals in Ilam Province were endowed with competitive advantage in three dimensions of durability and permanence, retention, and opportunities; however, they lacked competitive advantage in the dimension of individuals’ unique capabilities.

In the current work, a framework is presented for amine solvent selection in gas treating process. Since the appropriate decision making in this field affects the capital and operational costs, multi attribute decision making (MADM) techniques were used to rank alternatives. The determination of criteria and alternatives is the most important aspect in the MADM. Criteria were divided into two categories, namely physical and process, and twelve physical indexes and nine process indexes were detected. Mono-ethanol amine (MEA), di-glycol amine (DGA), di-ethanol amine (DEA), di-isopropanol amine (DIPA), and methyl di-ethanol amine (MDEA) are intended as alternatives. The importance of the criteria was expressed by weights, and the weights were determined by the analytic hierarchy process (AHP) method. The traditional Technique for Order Preferences by Similarity to an Ideal Solution (TOPSIS) method was applied to the physical criteria with crisp data. The modified interval TOPSIS technique was used to study the process criteria with interval data. The data of the criteria and alternatives were collected from Ilam Gas Treating Company, and the solution for sour gas sweetening was ranked by the proposed approach. Based on our computations, MDEA was defined as the best amine solvent with an average ranking of 1.5.

Nowadays, due to the huge effects of designing the supply network on the economic interests of organizations, the quality of providing appropriate services and customer satisfaction, the problem of network design is one of the most interesting and attractive issues of research in operations and management science. In this paper, a real-world manufacturing network is designed. The structure of this supply chain is such that the product is stored in the production facilities after production in the manufacturing plants and then transported to the retailers. Ultimately, customers will be able to address their needs by visiting retailers. In order to be real, fuzzy uncertainty is considered in the model parameters, and disruptions such as fire or power failure, etc. in factories and warehouses are considered simultaneously. Also, the problem has a multi-period time horizon and two goals are to minimize cost and maximize the coverage level of customers. To solve it, using CPLEX (GAMS) by ε-Constraint approach.

This research presents a mathematical model for performance-based budgeting and combines it with rolling budget for increased flexibility. The model has been designed by Chebyshev's goal programming technique with fuzzy approach. The parameters or coefficients of the model are derived by measuring the productivity of the organizations considering eight criteria. Data for calculating productivity indicators were collected from gas refineries of Iran in 2011–2015 and analysed by Excel and GAMS software. Then, the model was tested for determining the 2016 budget of those refineries. The model was solved by LINGO software by linking it to Excel. The solution of the model reduced 0.68% of the total refinery's budget compared with the actual budgets for 2016, which is higher than the annual budget of some of the companies in this group.

In this study we have used Collocation Method (COM) as a new method in the control and dynamics of reactor fields for solution of reactor point kinetics equations in the presence of step, linear and sinusoidal reactivities with six groups delayed neutron. The calculation code has written by MATHEMATICA software. This method in addition to the low time of calculations and convergence of solutions, it has high accuracy. The results of numerical calculations by COM compared with other numerical methods show that this method is efficient and accurate. Therefore, it can be used for dynamical computing at the startup stage of the reactor.

In this study, using a SU(1,1) Lie algebra in the Hamiltonian of Interacting Boson Model (IBM-1), we have calculated the energy spectrum of chain Barium isotopes ( 124-130). We have obtained the constants of this spectrum by solving the Bethe equation using the Least Squares method with the Newton-Gauss and Genetic algorithms. Finally we have compared the results of experimental spectra with theoretical spectra and undefined levels of these isotopes were calculated. The results showed that the genetic algorithm has a lower standard deviation compared with the Newton-Gauss algorithm, and also the results of experimental spectra are in good agreement with the theoretical spectra.

Today, sustainable development is one of the important issues in regard to the economy of a country. This issue magnifies the necessity for increased scrutiny towards issues such as environmental considerations and product recovery in closed-loop supply chains (CLSCs). The most important motivational factors influencing research on these topics can be considered in two general groups: environment-friendly legal requirements and cost efficiencies. The most important elements in the closed-loop supply chain include collection centers and treatment centers. This paper intended to design a network according to the mentioned principles. In this regard, three types of product treatment centers were taken into account: physical, biological, and thermal. The network design was made via a new mixed multi-objective nonlinear mathematical model of integers. In this model, three objective functions were considered that included profit maximization, pollution minimization, and the minimization of the number of facilities under construction. The model was obtained after determining the number of collection and treatment centers, the number of containers for storage of different waste materials, the amount of waste sent from collection centers to the treatment centers, and the areas covered by collection centers. Due to the conflicting objective functions, a corrected NSGAII algorithm was used to solve this model. The change applied in the mentioned algorithm was made to determine the appropriate amount of the crossover percentage. The improvement in the performance of the proposed solution algorithm is shown using a numerical example. To prove the improved performance, a T-test was used to compare the means between the two populations. To select the optimum answer from the Pareto solution set, indices of D, S, and solution time were used and solved with TOPSIS.

A new mathematical model based on the alternative process routings in presence of a queuing system in a dynamic cellular manufacturing system has been proposed in this paper.This model integrates two problems of cell formation and inter-cell layout and also an efficiency factor which is defined for minimizing the cell load variation through the maximizing the busy time for all machine types. In order to evaluate the performance of proposed model, some numerical examples are generated randomly and solved using GAMS optimization software suitable for MIP and MINLP models. The Baron solver which is capable of solving both linear and nonlinear model is implemented. Experimental results verify the applicability of proposed model in every industrial plant which implements a CMS. Moreover, based on the sensitivity analysis, the queue system has significant impact on overall system efficiency. In other words by increasing the part arrival rate the machine busy time is increased strictly.

Inventory management in production-remanufacturing system has been receiving a great deal of attention in recent years. In literature review, production environment is composed of two sections. The first section is included: production process, remanufacturing process and other options considered in reverse logistics. The second section is included: collection and sorting processes. Determination of sale price in inventory system is one of the most important issues in the first section and determines the acquisition price is one of the topics discussed in the second section. In this paper, we consider the two issues together. At the beginning of this article, an inventory model with product return is presented. To solve the model, genetic algorithm (GA) and simulated annealing (SA) are used. The results of the model solving are production and remanufacturing quantity and acquisition and sale prices. It is noteworthy that we have considered the quality level in modeling process.