linear programming model

The present study aimed to optimize the income basket of Ansar Bank, and for this purpose, the main objective and collective purpose of Ansar Bank has been identified. Then, in sub-descriptions, each objective is considered as a function of income basket items and the coefficients of these substructures were estimated using analytical hierarchy process (AHP) econometric method and linear planning method. The main purpose of the complete linear planning model will form. The results show that the benefit of optimal granting facilities in the Ansar Bank's income basket is 64%, while the benefits of granting facilities in the Ansar Bank's income basket are currently 72%. Also, the profit from investment and optimal deposit in the income basket of Ansar Bank is 22 percent, which is currently 14 in Ansar Bank's income basket now. The requirement for its optimal level in the income basket of the Ansar Zero Bank is obtained, while the boundary in the income basket of Ansar Bank is one percent. There is also an optimal amount of fees in the Ansar Bank's income basket of 11%, in which the Bank of Ansar Bank is 7%,

In today's complex world and in order to increase competitiveness, planners in the manufacturing systems have focused on product distribution and collection of used products. In this paper, the closed-loop supply chain scheduling problem is investigated for the first time. A comprehensive and integrated model is presented for production scheduling, delivering products to retailers using limited-capacity vehicles, and pick-upping end of life products in order to recycle and reuse in supply chain. The aim of this problem is to minimize maximum tardiness. Due to the fact that this problem is NP-hard, a genetic algorithm is presented to solve the large-size instances by obtaining near-optimal solutions. To illustrate the importance of the problem under consideration, a case study of the motor oil supply chain is presented.

The purpose of this paper is decomposing total factor productivity growth with reconciling both of the input- output and linear programming models in general equilibrium framework rely on the shadow prices of production factors as their real values in an open economy and studying its performance in Iran. For this purpose, input- output tables of central bank of Iran aggregated in 7 sectors are used for years 1367 and 1378. In this research, we decomposed total factor productivity growth to three factors named technical changes, terms of trade effects and efficiency changes which are reached by solving a linear program of maximization of domestic final demand using the framework of Raa and Mohnen (2002) paper. In this regard, the main question is that which of the three factors listed above is the major factor of total factor productivity growth in Iran? Based on the results, technical changes with share of 91 percent were the major factor of total factor productivity growth in Iran in our study period. 

. The control and planning of operating rooms have became more and more important for hospital managers. Nowadays, the operating rooms, as key resources, often lead to a great time waste. So, appropriate scheduling of operations in order to increase the efficiency of the operating rooms, are significant research topics in medical care. In this study, a new linear programming model has been developed for the assignment of patients to the operating rooms. Since the duration of surgical procedure is a stochastic parameter, in this paper a two-stage stochastic programming model has been presented in addition the deterministic model. These presented modelssimultaneously investigate the scheduling of surgeries and allocating them to the surgery rooms. The aim of this study is to minimize the cost of assigning patients to unspecialized rooms and reduce the cost of doctors’ idle time per working shifts by taking into account the constraints. The suggested models were applied for the surgery department of Ghaem hospital of Mashhad and solved by ILOG CPLEX 12.6.1 Microsoft Visual Studio environment. The results show that the deterministic proposed model increases the average efficiency of hospital to 38.275% and the stochastic model increases the average efficiency to 85.32%.

One of the most important challenges in the stock market for investors is selecting Portfolio. This study by considering the financial ratios as evaluating indicators tries to determine appropriate model for investment decisions in stocks. In this study, the combination of respectively models, linear regression, multi attribute decision making and linear programming were used to forecast the future of financial ratio trends, ranking companies and asset allocation. In the first step of study, after selecting 17 financial ratios and indicators as variables of the hybrid model, their values from the first quarter of 2007 to the first quarter of 2015 was calculated for companies included in the sample. Then by using the moving average with exogenous inputs and Auto Regressive Moving Average with exogenous input, these variables were predicted for the studied period (second quarter 2015). In the next step, we used Shannon entropy to determine the weight of indexes and the grey relational analysis for ranking companies. Finally, by using a linear programming model, a model was developed to select the optimal portfolio. According to this model, a portfolio of stocks formed and by using the Sharp ratio, its performance was compared with the overall index and the top 50 index. The results showed that the hybrid model has had a better performance than the overall index and the top 50 index, in the period of the study.

In this article, we will review and compare all defined kinds of variables in modeling section of operations research process. Since in real world, problems related to managerial decision makings because of humanities and complex factors like social, psychological, economical, political and etc, have high degree of uncertainty. It seems that available kinds of variables in literature are unable to explain all possible states of real conditions; so we will introduce new variables such as second class random variable, random uncertainty variable, uncertainty fuzzy variable, fuzzy uncertainty variable and second class uncertainty variable. Also, we will propose generalization of different combinations of variables to higher levels. Then, in base of second class uncertainty variable, we will provide new versions of linear programming model titled second class uncertainty and full uncertain linear programming models. In continue, we will present a numerical example from uncertain portfolio selection problem to verify proposed model. After that uncertain optimal solutions will attain by disciplined convex programming software.