نشریه تصمیم گیری و تحقیق در عملیات
سال هفتم شماره 1 (بهار 1401)

The aim of this paper is to propose a new extension of Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method to be applied with Hesitant Fuzzy Numbers (HFNs).

At first, the uncertainty of all enteries of evaluation matrix have been modeled by HFNs. Then, each step of the standard model of TOPSIS method will be updated, using the newly introduced HFNs’ mathematical tools, such as distance measures and aggregation operators of HFNs.  The proposed method will be used to solve a Multi-Attribute Decision Making (MADM) problem. Finally, the credibility and comparison analysis of the obtained ranking order will be discussed.

In this paper, the TOPSIS method as a popular method for solving MADM problems has been developed to be applied with HFNs.

In this paper, the TOPSIS method as a popular method for solving MADM problems has been developed to be applied with HFNs.

Determining efficient solutions of the Interval Multi Objective Linear Fractional Programming (IMOLFP) model is generally an NP-hard problem. For determining the efficient solutions, an effective method has not yet been proposed. So, we need to have an appropriate method to determine the efficient solutions of the IMOLFP. For the first time, we want to introduce algorithms in which the strongly and weakly efficient solutions of the IMOLFP are obtained.

In this paper, we introduce two algorithms such that in one, strongly feasible of inequalities and in the other, weakly feasible of inequalities are considered (A system of inequalities is strongly feasible if and only if the smallest region is feasible, and a system of inequalities is weakly feasible if and only if the largest region is feasible). We transform the objective functions of the IMOLFP to real linear functions and t‎hen convert to a single objective linear model and then in each iteration of the algorithm, we add some new constraints to the feasible region. By selecting an arbitrary point of the feasible region as start point and using the proposed algorithms, we obtain the strongly and weakly efficient solutions of the IMOLFP.

 In both proposed algorithms, we obtain an efficient solution by selecting the arbitrary points, and by changing the starting point, we obtain a new point as the efficient solution.

In this research, for the first time, we have been able to obtain the strongly and weakly efficient solutions of the IMOLFP.

One of the major challenges facing performance appraisal based on the Balanced Scorecard approach is the lack of uniform integration and inference from understanding some of its indicators, which depend on the mental models of managers. Lack of proper understanding of organizational strategies and lack of common vision of these strategies is another challenge that must be minimized in order to properly implement this model. Therefore, the present study has tried to investigate the effect that decision makers' mental models have on performance appraisal indicators from the perspective of balanced scorecard and consequently on organizational performance, in order to create more development and enrichment in the scorecard model. Balanced in order to reduce the perceptual shortcomings and torsionality of some indicators in it, provided the possibility of better performance measurement in accordance with the mental models of evaluators and decision makers.

In this regard, the data required for the research were distributed and analyzed through two stage of pls software and it is a researcher-made questionnaire among the managers of the Refah Bank in Gilan province.

 The validity and reliability of the questionnaire were 0.895 and 0.603, respectively, and Cronbach’s alpha was 0.850. The results of this study indicate a strong and direct relationship between mental models and performance appraisal indicators from the perspective of a stable balanced scorecard as well as organizational performance. The dependence of more than 80% of the organizational performance variable on the subject mental model also shows the high impact of this index on it.

  The existence of an intermediate relationship between the index of mental models, and other sights of the stable balanced scorecard approach showed that this is an important factor affecting organizational performance and can improve and enhance organizational performance by influencing the views of the balanced scorecard.

In this research, the effect of scale-time volatility of assets (currency, stocks and housing) on the efficiency of the banking network in the period 1399: 4-1388: 1 has been studied quarterly using the Markov switching model.

In this study, we first calculate the efficiency of the bank network using the data envelopment analysis model with bootstrap data. Then, the volatility of asset market (exchange rate, stock market index and housing price index) extracted using the wavelet conversion pattern and examines the impact of volatility of asset market on the efficiency of the country's banking network in the form of the Markov switching model and observing their effect on different levels of efficiency.

The average efficiency of the country's banking network in the study period has been about 56.1%, which indicates that efficiency has not been appropriate. The short-term volatility of the exchange rate in the state that the  efficiency of the bank network and the high regime has a negative and significant effect, but if the long-term exchange  volatility, regardless of the regime and the level of banking network  efficiency, has a negative and significant effect. The short-term volatility of the stock market index have had a positive and significant effect on the level of low banking network efficiency. But if volatility are continued in the stock market, regardless of the level and regime, the efficiency of the banking network has a negative and significant effect. The short-term  volatility in the housing market have had a positive and significant effect on the level of bank network efficiency but in the opposite side of the long-term volatility in this market and in a high level of bank network  efficiency, it can lead to significant reductions. Therefore, by stabilizing the economy (lack of large exchange rate, stock index and housing), it can be expected to improve the efficiency of the country's banking network due to its level and regime.

One of the issues that can be important in policy making perspective is to consider the impact of volatility of assets market in different time periods on different levels of banking network efficiency. Because they may have a different impact on different levels of bank network efficiency as well as different periods of volatility of assets market.

Outsourcing is a prevalent strategy in the industry and business, which can enhance the performance of a company and rectify its constraints. This strategy can be integrated into various managerial aspects of a company, particularly the scheduling subject. In this paper, a single machine scheduling problem is investigated in which a set of jobs can be outsourced in a batch to a single subcontractor. It is supposed that the outsourcing time and cost of a job are proportional to its in-house processing time. In addition, a fixed logistics time and cost are also considered for the outsourcing batch. Moreover, the problem objective is to minimize the sum of the total completion time of the jobs and the total outsourcing cost.

To solve the problem, a set of optimal properties of the problem solution are proven via a lemma and a theorem to determine the optimal solution of the problem. Moreover, some computational experiments are also conducted at the end of the paper to examine the effect of the outsourcing strategy in the addressed problem.

By the developed solution approach, the structure of the optimal solution is determined, using which the optimal solution of the problem can be chosen among a limited set of candidate solutions via some simple computations. Moreover, the computational results indicate the remarkable possible role of outsourcing in decreasing the value of the objective function of the problem.

In this paper, a new practical problem in the research area of scheduling with outsourcing is defined and its optimal solution is determined via a detailed analysis. Furthermore, using computational experiments it is shown that the outsourcing strategy can have a great role to attain the problem objectives.

Order picking operation is one of the most well-known labor and cost intensive internal logistics processes. Withdrawal of the order in response to customer need is defined in order to collect a set of orders from storage zone in the shortest possible time. The purpose of this research is to provide a scientific and practical basis considering the constraints that enforce to achieve an acceptable level of performance in order picking systems. This is done by building a Mixed Integer Linear Programming (MILP) formulation and developing an adapted solution method suited to the structure of the problem

First, by reviewing the literature in the field of order picking systems, sufficient knowledge has been obtained at the operational level, and with emphasis on warehouse management constraints, a MILP formulation is proposed by integrating order batching and picker routing. After validating the model and solving it through GAMS software, due to the nature of the problem, which is an NP-hard type, the problem is solved with an efficient algorithm, which is a grouping version of the league championship algorithm, and the results are compared. To develop the algorithm, operators are fit to the specific structure of the problem, i.e., the assignment of orders (items) to order pickers (groups)

Developing a multi-period MILP formulation for multi-trip picker routing, assuming for the first time the possibility of product replenishment and limited access to pickers. For large-scale problem instances, the league championship algorithm is used. The results indicate the effective capability and efficiency of this algorithm for solving large test problem instances.

The issue of multi-period order picking and multi-trip routing of pickers is considered for the first time ‎in this paper. Because of the limited number of pickers, this must be taken into account in modeling. ‎The assumption of product replenishment is also considered for the first time in this article and its ‎modeling has been done. In this way, orders enter the warehouse over time, during different periods, ‎and are placed in a predetermined positions. The limited access to pickers in each period is also ‎discussed for the first time in this paper. Finally, the objective function of minimizing the total ‎tardiness, which is in line with the needs of the industry, is also introduced in this paper. Regarding the ‎solution method, a league championship metaheuristic algorithm is presented which takes into ‎account the problem structure (which corresponds to the structure of grouping problems) and ‎solution generation operators have been developed to maintain the new solution.‎

Statistical Process Control (SPC) is a powerful set of problem-solving tools that stabilize production processes and increase the ability to produce high quality product. Classic control diagrams, using precise and definite data, place production processes into two groups: under control or out of control; while Fuzzy sets by defining continuous membership functions and using ambiguous, indefinite data, triangular and trapezoidal Fuzzy numbers, classify into these categories: under control, relatively under control, relatively out of control and out of control which express the quality level of the product more realistically.

This research is an applied and descriptive research with the aim of designing an applied model of Statistical Process Control by Fuzzy Mode and Middle Fuzzy and comparing its results with Classical Method in Dadash Baradar Ind. Co. in Tabriz. This method of data collection to run the model follows the sampling system at the inspection station and is in the form of 30 samples of 50 chocolates.

According to the seven defects of chocolate, which include: color, taste, acidity, sugar blossom, tissue factors and foreign substances, the nature of the produced chocolate was determined. In the Classical Method, 28 cases under control and only 2 cases out of control were identified, but in the study with Fuzzy SPC Method, 20 samples under control, 4 samples relatively under control, 4 samples relatively out of control and 2 samples were out of control.

Research results shows the sensitivity of the Fuzzy SPC Method compared to the Classical Method; as a result, identifying process changes is more accurate and faster, and accordingly practical suggestions have been provided to the company.

Risk parity is one of the stock portfolio selection models that has received a lot of attention since the US national financial crisis in 2008. The philosophy of this model is to allocate an equal amount of portfolio risk between the assets. In the present study, the portfolio selection model is introduced which is a combination of risk parity portfolio and factor analysis with the Markov regime-switching framework.

The portfolio selection model is introduced which is a combination of risk parity portfolio and factor analysis with the Marko. Regime-switching framework approach. Markov regime switching helps to make the covariance matrix in the objective function of the risk equality model dependent on the state variable and increase the stability of the portfolio. At the beginning of each investment period, the state variable is determined and the asset covariance matrix is calculated based on it and used in the risk equality model

The research portfolio consisting of 8 industries from the Tehran Stock Exchange in the period 1390 to 1399 shows that this portfolio has a higher sharp ratio than the mean-variance and equally weighted portfolios in market declines, it is more durable and produces less damage.

The innovation and importance of research is robustness of risk parity portfolio by considering the covariance matrix parameter with factor analysis in Markov regime-switching framework. Thus, it is expected that in different market situations, expectations from the stock portfolio will be more consistent with reality and less losses will be produced in market declines.

In classical data envelopment analysis models, a production system for measuring performance is considered as a black box and no attention is paid to the internal structure of decision-making units in the process of evaluation performance. However, it is important to consider the internal structure of the units to identify sources of inefficiency to calculate efficiency. On the other hands, the observed values of input and output data in real world problems are sometimes imprecise and vague. Therefore, in this paper, the network data envelopment analysis model is used in order to evaluate the performance of decision-making units with a two-stage structure in a fuzzy environment in which input and output values are displayed in terms of triangular fuzzy numbers.

To solve the fuzzy two-stage data envelopment analysis model, the fuzzy arithmetic approach is used and a lexicographic optimization method for calculating the fuzzy efficiency of processes and the fuzzy efficiency of the system is proposed.

The main advantage of the proposed approach over the exsiting approaches is that it solves fewer models for finding fuzzy efficiency.

The application of the proposed model is explained by evaluating the performance of 24 insurance companies.

Designing a logistic network is a vital and strategic issue that provides the optimal platform for effective and useful management of supply chain. For this purpose, in this paper, a multi-echelon, multi-product, multi-period and multi-objective sustainable dual-channel closed-loop supply chain network has been designed taking into account the technology of RFID. Simultaneously this model seeks to maximize the profits and social responsibility of the supply chain network while it minimizes the whole delay in delivery time and environmental pollution. Also, because definitive models are incapable of understanding the complexities of real-world applications, so this paper also addresses systemic and environmental uncertainties.

In this study, the scenario-based stochastic robust programming optimization technique is used to deal with the uncertainty of the parameters and to deal with the uncertainty of the parameters, and due to the multi-objective model and for validation and model exact solution in small dimensions of a new robust augmented ε‑constraint method (AUGMECON‑R) is used to achieve the best balance between the objectives. Also, since the problem is of np-hard class, two NSGA-II and MOPSO algorithms were used to solve the model in larger dimensions.

The results show that this model has acceptable efficiency that due to the uncertainty of some parameters.

The proposed model includes mathematical formulas in a certain and robust state that allows the establishment of several complicated characteristics in the above text along with direct and indirect selling channels and repairing centers and secondary costumers create the new design of supply chain that can be supreme model for the managers and professionals with the wide application especially from strategic view.