In this paper we investigate the issues of data classification (as one of the branches of data mining science) in form of multi-objective MATHEMATICAL programming MODEL. The MODEL that we present and investigate is a MODM problem. First time, based on support vector machine (SVM) idea (To maximize the margin of two groups), a multi-criteria MATHEMATICAL programming MODEL was proposed for data mining problems to classified instances in two separated group based on two goals of data discriminate (To maximize the distance between different groups and to minimize the misclassification of observations). Since then, some people have been working on developing the classification MODELs based on MATHEMATICAL programming methods. Simultaneously and also independently, individuals worked on support vector machine methods to improve them. Regarding to the same philosophy of these two groups of optimization methods, in this paper, to fill the gap between these two research paths, we use the updated and improved SVM methods to present a MODEL for classification in data mining based on multi-objective programming.

The control systems and related structures have an important role in water distribution in irrigation networks, and the success of irrigation networks highly depends on their proper functioning. Control structures behave differently under different control systems. Providing higher flexibility in water delivery and reducing water losses by application of downstream control systems is an important factor for performance improvement of irrigation networks. One of the downstream control systems which is suitable for sloping canals is constant volume control system named BIVAL system. In this system while the water volume in canal reaches is kept constant, demand variation is satisfied quickly and canal earthwork is reduced. In order to study hydraulic behavior of irrigation canals in coordination with control systems which is unsteady, using hydrodynamic MODEL is inevitable. In this research MATHEMATICAL MODEL of constant volume downstream control system (BIVAL) is developed and linked with ICSS MODEL. For calibration and evaluation of developed MODEL on local and global scale, El-RI branch of Dez canal network in Iran and the standard canal introduced by ASCE are chosen respectively. Each system was calibrated in wide ranges of different flow rate and different values of numerical coefficients and the proper coefficients were derived. Afterward each one of control systems were operated under different operational schedule and performance indices, MAE (Maximum Absolute Error), IAB (Integral of Absolute Error) and SRT (System Response Time) in 5% and I% levels were computed. Performance indices for a reach with highest variation derived as 2.57, 0.28 and 0 respectively. Depth, flow rate and gate opening fluctuations for local testing, and depth fluctuations for global testing at middle of reaches are calculated and depicted. Performance indices and hydraulic behavior of the system indicates proper functioning of the developed MODEL.

In this research, the most important components of an obstacle-free airport design criteria such as; length and width of runway, safety area, stop way area, and dimensions of clear way, Including horizontal, conica, approach, and transitional surfaces are integrated into a MATHEMATICAL MODEL. Since high rise buildings and towers have always created problems for airport designers, in this research, a MATHEMATICAL and computerized MODEL has been developed to resolve these difficulties. The application of the developed MODEL covers various categories of airports, including domestic and international. The methodology of research is such that all the obstacles surrounding the runway are controlled. In this way no point will be considered as an obstacle towards these surfaces. Should there be any obstacle, a solution will be recommended to resolve the problem. The standard code of practice used for this software complies with the documents of International civil Aviation organization 9ICAO). The developed software operates on Windows 98 and over platform based on Visual Basic 6.

Due to the widespread outbreak of Covid-19, many of the world's top universities have decided to hold the next semester virtually. In our country, too, the forecasts show a red situation for some areas in terms of corona prevalence. Due to the large number of students living in these areas, planning for the next semester of universities should be more focused on e-education. According to the instructions of the Ministry of Science, Research and Technology of Iran, the next semester should be implemented in two ways, including e-learning and face-to-face education. In face-to-face education with the requirements of the educational space and classrooms, students are divided into two sub-disciplines A and B. The students in each category will be present in the class in different weeks so that it is possible to implement health protocols in the educational space and classrooms. In this paper, to determine the number of students and classes for both sub-disciplines A and B in face-to-face education, a MATHEMATICAL optimization MODEL in the form of nonlinear programming with integer variables is proposed. In the objective function of the MODEL, the distribution of students in the educational space and classrooms is considered in such a way that the maximum possible dispersion is possible to prevent the spread of coronary heart disease. In this MODEL, class capacity constraints as well as constraints for holding classes on even days (Saturday, Monday), odd days (Sunday and Tuesday) and Wednesday are considered. This MODEL has been implemented for allocating classes in the Faculty of Statistics, Mathematics and Computer of Allameh Tabataba’ i University and its use has brought satisfactory results for decision makers.

Designing and manufacturing of technical systems and devices in refineries, oil and gas pipelines and gas booster stations is associated with huge costs from an economic point of view. Hence, managers at industry section, especially oil and gas industry, seek ways to control the production and distribution costs. Generally speaking, at distribution section, selection of operational appliances by operators in gas booster stations to be run, would be done without considering various kinds of cost. In this research, a deterministic mixed integer program is presented to minimize the operational costs in gas booster stations of a gas distribution network. The objective is to select operational appliances, turbo-compressors here, such that minimize the operational costs while customer demands are met. Operational costs are include consumed fuel costs (fuel exploded in gas turbine combustion chambers to yield the torque power to run the gas compressor), maintenance and repair costs, startup costs (generally the electrical costs used for running the electro air compressors which provide the compressed air), and penalty costs. Considering the gas transmission operating region no.9 as a case study, the result is that the MODEL could minimize the total costs about 14% in comparison with the selection of two chief operators.

Maintenance routing is an important and complicated issue in aviation systems. Determining factors affecting delay and cost of flights is important as they cause customer dissatisfaction. Ramping and maintenance directly affect flights delay and cost. In this research، two novel MODELs on maintenance routing based on flying time (not necessarily duty day) and ramp scheduling are developed. The objectives are cost and delay minimization. The MATHEMATICAL MODELs are solved using GAMS and sensitivity analyses are presented. The result of sensitivity analysis shows that an increase in the number of aircraft in maintenance MODEL reduces cost and an increase in the number of machines in ramping MODEL reduce delays. So the result shows good performance of the MODELs in reducing costs and delay.

In this paper we propose a multi-objective MATHEMATICAL MODEL to aid the marketing team of a company in customer service marketing. Customer reflects to the services provided by a company, and the reflections affect the profit of the company. Thus, the services can be evaluated by the customers to imply the company's performances. First, the services are purified based on the opinions of the customers conducting a survey study by a questionnaire. The service purification is carried out using statistical hypothesis testing. The remained services are then assessed regarding time, cost and quality objectives constructing a multi-objective MATHEMATICAL MODEL. Then, a multi-objective MATHEMATICAL MODEL is utilized to determine the services with more profits. Analytic hierarchy process (AHP) is applied to solve the multi-objective MODEL. The applicability and validity of the proposed mechanism is illustrated in a case study.

The role of agriculture sector is important in earning foreign exchange. To sell products in international market, they must be competitive. This study investigates comparative advantage in Mazandaran province, by using common indices and linear programming method in 2006-2007. In the process, dollar and euro were used. The results of linear programming showed that among crops which had comparative advantage, rice, irrigated yam, irrigated and rain fed barley, rain fed soy been, irrigated tomato and rain fed lentil were in optimum MODEL. Most limited factor of production was land. The results indicated that adding one hectare to irrigate and rain fed land, would increase, net social profit by 25 and 18.5 million Rials, respectively. Sensitivity analysis for outputs and inputs was done individually. Estimation of MODEL by using dollar showed similar results with euro. Finally, based on the results, development of rice and oilseeds was recommended.

Current drug-eluting stent (DES) technology is not optimized with regard to the pharmacokinetics of drug release, more research on the drug-eluting stent design and flux of drug release to the arterial wall is necessary. Considering a three-dimensional (3D) cylindrical MATHEMATICAL MODEL, a novel free drug mass transfer release has been formulated and applied for better estimation of the drug concentration in the tissue. The transport equations involved both convection and diffusion equations. Besides, a reversible reaction in the arterial wall was considered. The present MODEL was solved by an appropriate numerical simulation method and the predicted results were compared with in vivo data. To find out the rate-limiting step, the time scale analysis was also applied. The obtained results showed that the binding process is more limited by convection and diffusion, where convection is the rate-controlling step. It is also demonstrated that the presented approach has advantages over the prior free drug mass transfer MODELs, including better data prediction and satisfying mass transfer consistency.