International Journal of Applied Operational Research

Evaluation model for the human resources management with analytic hierarchy process (Part: Power distribution companies)

H. Nadiheidari

The purpose of the present study is to present an integrated model for evaluating the comparative performance of units in power distribution companies. For this purpose, BSC technique is used to classify evaluation indices, statistical analysis is used to evaluate the significance and the significance of the identified indices, and finally, fuzzy AHP multi-criteria decision-making technique is used to compare and rank units. In this paper, we will discuss the research method. The research method is based on the purpose and method of data collection, the tools and methods of data collection, the statistical population, and the sample. Then the performance evaluation indices of the units are identified using 4 perspectives of BSC, a review of research literature, a meeting with organization managers, and a research questionnaire designed to identify essential indicators from the experts' point of view of the organization. The validity and reliability of the questionnaires are also described. Finally, methods for analyzing the results are presented. The purpose of this study is applied research and the results of this study can be used by power distribution companies to evaluate the performance of operational units and ultimately strategic planning to improve performance. It is also descriptive in terms of data collection and survey type. For this purpose, after creating the appropriate hierarchy of problems using BSC technique, AHP multi-criteria decision-making technique is used to determine the weight and priority of each indicator with a team of experts and managers of the organization.

A two- phase approach for solving fuzzy flexible linear programming problems with fuzzy objective coefficients

S.H. Nasseri

In this paper, new concepts of α -feasibility and α -efficiency of solutions for fuzzy mathematical programming problems are used, where α is a vector of distinct satisfaction degrees. Recently, a special kind of fuzzy mathematical programming entitled Fuzzy Flexible Linear programming (FFLP) is attracted much interest. Using the mentioned concepts, we propose a two-phase approach to solve FFLP. In the first phase, the original FFLP problem converts to a Multi-Objective Linear Programming (MOLP) problem, and then in phase II a weighting technique for the reduced program is introduced. We saw that it was observed that using this concept as a generalization of the parametric approach in linear programming provides a more appropriate tool for modeling real problems and improving the solving process. Thus, by using this two-phase approach, we achieve better utilization of available resources. Further, the solution resulting from these two approaches is always an α -efficient solution. Finally, an example in the real world is described to express this approach.

A new source of inefficiency due to the inappropriate choice of price in data envelopment analysis

E. Rezaei Hezaveh

Data envelopment analysis (DEA) is a useful tool for identifying well-performing (efficient) decision-making units (DMUs). In DEA, those units that are not placed on the efficiency frontier are considered to be inefficient units. Identifying inefficiency sources can help turn the units into more efficient ones. Therefore, studying inefficiencies is of utmost importance. The present paper aims to propose a cost production possibility set in a non-competitive environment (where prices can vary from one DMU to another). We compare the three PPSs so that we can introduce a new inefficiency source for DMUs based on the inappropriate choice of price by evaluating DMUs and comparing them with the existing cost production-possibility set frontier. And as a result, optimizing these price vectors can remove or, at least, reduce inefficiencies and create more efficient units.

Determining a common set of weight by reducing the flexibility of weight profile

A. Pourhabib

Data Envelopment Analysis (DEA) is non-parametric mathematical programming for measuring the performance of a set of homogeneous decision-making units (DMUs). Standard DEA models usually result in several efficient units, so, picking the best unit among efficient units has been one of the most challenging subjects in DEA literature. With reference to various researchers, the common set of weights (CSW) approach has been intriguing among them. This paper discusses a mechanism for detecting a common set of weights which is managed to be always positive and prevents weights dissimilarity. Employing this common set of weights can determine the efficiency score of each unit and finally rank them based on their obtained efficiency score. Equally, the proposed model not only provides the closest targets, but also minimizes the deviations of actual DMUs and extreme efficient units. In order to verify the proposed approach an empirical example of Iranian electricity distribution companies is explained.

Wavelet transform and ANFIS network-based prediction technique for forecasting confirmed cases of Covid-19 in Iran

M. Faridi Masouleh

Coronavirus disease 2019 (COVID-19) is a contagious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The first case was identified in Wuhan, China, in December 2019. The number of confirmed cases is increasing daily and reached 101 million on 28 January 2021. This paper attempts to propose a new hybrid intelligent method for the prediction of confirmed cases of COVID-19 in the upcoming ten days based on the previously confirmed cases recorded. To forecast future cases, wavelet full decomposition of time series analysis served as input data for Adaptive Network-based Fuzzy Inference System (ANFIS). In addition, to tune the ANFIS membership functions, Quantum-behaved Particle Swarm Optimization (QPSO) was used. During the data preprocessing phase, all kinds of Wavelet Transform functions were tested for the best result. The proposed method was found to be very efficient in forecasting confirmed cases of COVID-19 in the upcoming ten days.
The proposed model is an improved adaptive neuro-fuzzy inference system (ANFIS) using QPSO and Wavelet Decomposition. The WT-QPSO-ANFIS model is evaluated using the World Health Organization (WHO) official data on the outbreak of COVID-19 to forecast the confirmed cases in the upcoming ten days. More so, the WT-QPSO-ANFIS model is compared to several existing models, and it showed better performance in terms of Mean Absolute Percentage Error (MAPE), Root Mean Squared Relative Error (RMSRE), Root Mean Squared Relative Error (RMSRE), coefficient of determination (R2), and computing time.

Modifying the resource portfolio and expenses of Iranian bank branches using multi-objective optimization models

R. Kiani Ghalehno

One of the serious challenges in financial and credit institutions is the reform of the financial portfolio of branches with negative returns. The financial portfolio of banks has a combined structure of deposit attraction and investment, the main purpose of this study is to modify the deposit portfolio and facilities of branches so that the outcome of income and expenses tends towards positive returns.
Inspired by the basic model proposed by Markowitz [1], this study provides a model for financial and credit institutions tailored to their needs. model parameters are: The current portfolio status of a branch, along with other factors that affect portfolio performance. model variables are: Changes that will be made to the numerical values of the initial portfolio to modify the model from negative to positive returns. In order to be able to modify the portfolio in multi-period, the one-period to multi-period model has been developed.
Countries like Iran, where government decisions affect interest rates on deposits and loans, and they have different types of deposits and loans with different rates, it is necessary to establish a logical correspondence between different types of deposits and facilities. The main finding of this research is to provide a model that can improve the branches that have a portfolio with negative returns, with an achievable program, while observing the government and upstream constraints. The proposed models used for the Agricultural Bank of Iran , and the results have been analyzed. The results show that despite the restrictions that banks have to follow the orders of the government and the upstream, they have to create a domestic market and inject some kind of virtual deposit and loans, Reform the portfolio of branches with negative returns.