Iranian Journal Of Operations Research
Volume:13 Issue: 1, Winter and Spring 2022

In the traditional cost-efficiency model, the information about each decision unit includes inputs, outputs, and the input prices are fixed and specific. In practice, the price of the inputs often fluctuates at different times, and these prices for the decision-making unit are time-dependent. By the traditional method, the efficiency of decision units is impossible in the presence of time-dependent input prices. On the other hand, the exact method of cost-efficiency calculation is also difficult and time-consuming. In this study, a new method for calculating cost efficiency of decision making units with time-dependent prices during a period of time using numerical integral is presented. As the information of the decision-making units varies over time, a method for calculating their cost efficiency accurately is presented. however, the exact method is difficult or impossible to be solved in some cases. Therefore, in this study, an approximate method for calculating the cost efficiency in the given state is presented. This is a suitable replacement for the precise method. The efficiency of decision making units at different time is measured and the units are ranked using the proposed method. Finally, a numerical example is provided to indicate the method and compare it with the precise method. This study shows that the efficiency obtained by the approximate method is very close to the efficiency obtained by the exact method, and at the same time, the calculation speed increases.

Data Envelopment Analysis (DEA) is a nonparametric approach for evaluating the relative efficiency of a homogenous set of Decision Making Units (DMUs). To evaluate the relative efficiency of all DMUs, DEA model should be solved once for each DMU. Therefore, by increasing the number of DMUs, computational requirements are increased. The Cerebellar Model Articulation Controller (CMAC) is a neural network that resembles a part of the brain known as cerebellum. The CMAC network with a simple structure is capable of estimating nonlinear functions, system modelling and pattern recognition. Meanwhile, the CMAC approach has fast learning convergence and local generalization in comparison to other networks. The present paper is concerned with assessing the efficiency of DMUs by the CMAC neural network for the first time. The proposed approach is applied to a large set of 600 Iranian bank branches. The efficiency results are analyzed and compared with the Multi-layer Perceptrons (MLP) network outcomes. Based on the results, it can be seen that the DEA-CMAC results tend to be similar to those of DEA-MLP in terms of accuracy. In addition, the Mean Squared Error (MSE) in DEA-CMAC decreases much faster than that in DEA-MLP. The DEA-CMAC model takes 1008 and 1107 iterations to reach MSE errors of 2.03×10-4 and of 6.01×10-4 , respectively, while the DEA-MLP model takes 1190 iterations keeping the MSE error stable at 2.07×10-1 . Moreover, DEA-CMAC requirements for CPU time are far less than those needed by DEA-MLP.

This study evaluates the effectiveness of factors affecting the development of virtual education in the era of COVID-19 based on SCORM model from the viewpoint of students at Ferdowsi University of Mashhad. SCORM includes six dimensions that provide a comprehensive picture of the implementation process of a web-based learning management system. This research is a descriptive survey in terms of practical purpose and in terms of the data collection method. The statistical population of this research includes all postgraduate students in 2019. According to Morgan's table, the sample size is 370 people. The data collection tool is a researcher-made questionnaire, and the validity and reliability of the questionnaire are confirmed. The stratified random sampling method is used to distribute the questionnaires. One-sample t-test and "SPSS" software are used to test the research hypotheses. The results of the research showed that in the era of COVID-19 pandemic, virtual education has been effective and at a higher than average level in all six dimensions of SCORM standard (Accessibility, Consistency, Financial facilities, Durability, ability to run, reusability) and every six hypotheses are confirmed. Based on this, it is concluded that the virtual education programs planned at the Ferdowsi University of Mashhad are on the right path and can be strengthened and developed by receiving periodic feedback. Also, considering the successful performance of virtual education in the pandemic, in the future, this technology can be used as an effective supplement in educational and research activities in the university.

Here, we first associate a graph to a university course timetabling problem (UCTP) and use the components of this graph and some customary and organizational rules to transform the original large scale problem into some smaller problems. Then, we apply the branch and cut method to obtain the optimal solution of each smaller problem. Our presented approach enables us to apply exact methods to obtain high quality solutions for large scale UCTPs. Finally, we examine the numerical efficiency of the resulting algorithm.

This research was carried out with the aim of providing a comprehensive model for redesigning the organizational structure that fulfills the requirements of activity in the era of the fourth industrial revolution with the approach of developing smart business. The research was of a sequential mixed type of quantitative and qualitative type. In the quantitative part, which was conducted using a descriptive survey method, in the first stage, organization pathology and organizational design models were examined and identified through a systematic review of the research literature, and Burton's multi-contingency model, which simultaneously includes pathology and organization design, was selected. In the second stage, the researcher developed a questionnaire based on different editions of Burton's multi-contingency model, and the validity and reliability of the questionnaire (content validity using the Laushe method, face validity and construct validity using the confirmatory factor analysis method with Smart PLS software and reliability It was evaluated by the methods of Cronbach's alpha, composite reliability and divergent and convergent reliability of Fornell and Lockerre), the results of which indicate the high internal validity of the research and the validity of the tool designed in the society. Finally, a 90-item questionnaire was developed to measure 14 dimensions and 28 components, which was arranged in the form of a Likert scale and distributed among 263 managers and experts of Esfahan Steel Company, who were selected by stratified random method. After data collection and analysis, it was found that the different dimensions of the organizational structure of Esfahan Steel Company based on Burton's multi-contingency model are not located in one area and are scattered in four different areas of the diagram, and the dimensions of the structure are not proportional and aligned. In the future, in order to redesign the appropriate structure, the research was continued using the qualitative method. In this section, with the purposeful sampling technique dependent on the criterion among 30 academic and steel industry experts related to the subject, the most important dimensions of the organizational structure (using the fuzzy Delphi method and in two rounds) and the components of business intelligence (using the fuzzy Delphi method) and during three rounds) were determined. Then, by using the fuzzy Delphi technique during four rounds, which stopped at the Schmidt agreement criterion, a comprehensive model of organizational structure redesign with the approach of developing smart business was obtained. The findings showed that the most effective components of business intelligence include commercial intelligence, artificial intelligence, strategic intelligence, and competitive intelligence, which can provide suitable platforms and facilitators to achieve a suitable and intelligent organizational structure. The results show that the use of business intelligence factors consisting of strategic, competitive, commercial and artificial intelligence models are effective platforms for making appropriate decisions in order to make changes and redesign the organizational structure (organization plan) and create appropriateness and alignment. It is between dimensions with the aim of developing smart business.

The paper presents a scheme to supply energy consumers by using a multicarrier energy system (MES). Each MES unit consists of electrical vehicles (EVs), and combined heat and power (CHP) units, which are called energy hubs (EHs) hereinafter. The objective function minimizes the cost of energy of the whole system while considering power flow equations in electricity, heat, and gas grids, where constraints include technical index limits of MESs, EVs, and CHPs. The model has been formed as a non-linear problem (NLP), in the following, the present study proposes a linear programming (LP) model as a substitute for equations of the NLP method so that the global optimal solution is found with a low computation error. Furthermore, the demand parameters, electricity price, and characteristics of EVs are uncertain. To model these uncertainties, we adopt the point estimate approach. The case study of this research considers electricity, gas, and heating grids simultaneously. The energy hubs relate all three grids to each other. The method is tested on a system through simulation using GAMS software. According to obtained numerical results, the suggested LP approach reaches an optimal point with reduced computation time and low error compared to the original formulations. As a result, the indices of different networks are improved using power management of the energy hubs.

This study aims to develop a capacitated hub location-routing model to design a rapid transit network under uncertainty. The mathematical model is formulated by making decisions about the location of the hub and spoke (non-hub) nodes, the selection of the hub and spoke edges, the allocation of the spoke nodes to the hub nodes, the determination of the hub and spoke lines, the determination of the percentage of satisfied origin-destination demands, and the routing of satisfied demand flows through the lines. Capacity constraints are considered in the hub and spoke nodes and also the hub and spoke edges. Uncertainty is assumed for the demands and transportation costs, represented by a finite set of scenarios. The aim is to maximize the total expected profit, where transfers between the lines are penalized by including their costs in the objective function. The performance of the proposed model is evaluated by computational tests and some managerial insights are also provided through the analysis of the resulting networks under various parameter settings.

In Fisher's and Arrow-Debreu's market equilibrium models with linear utilities, a set B of buyers and a set G of divisible goods, suppose that there are some buyers with surplus money w.r.t current prices of goods. If there does not exists an equilibrium, then, there are some buyers with surplus money w.r.t the given prices. A set of buyers with surplus money called a violated set. Computing this set helps to find the set of buyers with maximum surplus money w.r.t the given prices. In this paper, two new kinds of violated sets are defined, which called maximum proportion and most violated sets. We present an algorithm to compute a maximum proportion set, which runs in at most |B| maximum flow computations. Also, we show that the set of all buyers B is a most violated set.

Cost efficiency in which cost coefficients are given for some inputs (cost coefficients can be different for disparate decision-making units (DMUs)) is one of the most important concepts in data envelopment analysis (DEA) to analyze the performance. Moreover, in some occasions, the cost performance and changes of input measures should be addressed while the convexity property is violated. Therefore, in this paper, first a DEA model is provided to assess cost efficiency based on the free disposal hull (FDH) model. Then, by considering cost and technical efficiencies achieved, a multi-objective problem called the inverse FDH cost model is presented to determine input values based on output changes while the cost and technical efficiency levels are preserved. The multi-objective problem is computed applying two approaches. Also, a dataset from the literature is presented to show the performance of the proposed method. For this purpose, we used the data of six banks in different countries. We added 2% to the outputs and analyzed the inputs with two models. In the first model, we used cost coefficients for weights, and in the second model, we used the same weights. Contrary to forecasts, some entries have decreased and others have increased. But from the results, we have noticed that the first model is more realistic because most of the solutions have increased in this model.

Today, a high volume of multimedia information is transmitted in computer networks, such as the internet, that the requirement for achieving high security level against unauthorized access. the visual secret sharing scheme is a cryptographic system without requiring a secret key that is able to encrypt information in a multi - user computer network. in this research, a visual secret sharing scheme including two strategies for binary communications and multiple relationships were considered. in binary communications, an entity plays a role in the role of the server and an entity in the role of the client 's service in this strategy using a network - based visual secret sharing scheme ( 2 , 2 ) a secure approach to establish double relations where the provider entity is sending confidential information after authentication of the client 's service. then, two main phases of registration and verification are performed on the basis of the visual secret sharing scheme based on random networks. in tuple communication ( n , n ) an entity plays a role in the role of the server and several entities in the role of the service, and then two main phases of registration and verification are executed.

Recently, Multi-objective optimization by ratio analysis (MOORA) as a new and efficient Multiple-criteria decision-making (MCDM) method was applied in different areas for ranking alternatives and choosing the best ones. MOORA method evaluates the studied options by using positive and negative criteria. In this paper, a literature review is presented to study the MOORA methodology and its applications. So, all published papers in Science Direct journals are investigated and categorized from different perspectives (application area, journal of publication, year of publication, authors’ nationality, and type of data in form of fuzzy /crisp). The papers covered several filed: material selection, energy, welding process, and surface roughness, automotive and wire, fuel selection, logistics and transportation, heat transfer, optimization, and other topics. It is hoped that the study is useful for researchers and also a useful reference for practitioners and academics to improve their future research. The highest amount of using the MOORA method with the number of 15 articles is related to material selection, which shows the importance of using the MOORA method for material selection. And the lowest amount of using the MOORA method with the number of two articles is related to fuel selection. The present study was able to provide a framework for future research by reviewing the MOORA method. The results show that the MOORA method is one of the most efficient methods for evaluating options in different fields, which can be used in different areas.

One of the most useful tools in Operations Research (OR) which is essentially applied to evaluate the performance of treated Decision-Making Units (DMUs) is Data Envelopment Analysis (DEA). Because of in the current decades, DEA models have been used and extended in many disciplines and hence attracted much interests. The traditional DEA treats DMUs as black boxes and calculates their efficiencies by considering their initial inputs and their final outputs. Since, in the real situations, input data are included some uncertainties, hence in this study we consider a DEA with fuzzy stochastic data and suggest a three-stage DEA model by taking into account undesirable output. To achieve this aim, an extended probability approach is applied to the reform of three-stage DEA models. Finally, we give an illustrative example by considering a case study on the banking industry.