DORA :: Browsing by Author "Hashemi, S.S."

Browsing by Author "Hashemi, S.S."

Now showing 1 - 15 of 15

Metadata only
Bi-Objective Mean-Variance Method Based on Chebyshev Inequality Bounds for Multi-Objective Stochastic Problems
(edp science, 2018-11-28) Amoozad Mahdiraji, Hannan; Razavi Hajiagha, S.H.; Hashemi, S.S.
Multi-objective programming became more and more popular in real world decision making problems in recent decades. There is an underlying and fundamental uncertainty in almost all of these problems. Among different frameworks of dealing with uncertainty, probability and statistic-based schemes are well-known. In this paper, a method is developed to find some efficient solutions of a multi-objective stochastic programming problem. The method composed a process of transforming the stochastic multi-objective problem to a bi-objective equivalent using the concept of Chebyshev inequality bounds and then solving the obtained problem with a fuzzy set based approach. Application of the proposed method is examined on two numerical examples and the results are compared with different methods. These comparisons illustrated that the results are satisfying.
Open Access
DEA with common set of weights based on a multi objective fractional programming problem
(2014) Razavi Hajiagha, S.H.; Hashemi, S.S.; Amoozad Mahdiraji, Hannan
Data envelopment analysis operates as a tool to appraise the relative efficiency of a set of homogenous decision making units. DEA allows each DMU to take its optimal weight in comparison to other DMUs while a similar condition is considered for other units. This feature threats the comparability of different units because different weighting schemes are used for different DMUs. In this paper, a model is presented to determine a common set of weights to calculate DMUs efficiency. This model is developed based on a multi objective fractional linear programming model that considers the original DEA's results as ideal solution and seeks a set of common weights to evaluate DMUs and increases the model's discrimination power. A numerical example is solved and the proposed method's results are compared to some previous methods. This Comparison has shown the proposed method's advantages in ranking DMUs.
Metadata only
Determining weights of fuzzy attributes for multi-attribute decision-making problems based on consensus of expert opinions
(2015) Razavi Hajiagha, S.H.; Amoozad Mahdiraji, Hannan; Hashemi, S.S.
An important objective of a group decision-making problem is to determine the weights of attributes that are given by experts participating in the decision-making process. Since different decision-makers have unequal importance in decision-making, a series of studies focused on finding a set of appropriate weights for experts participating in a decision problem. In this paper, the problem of weight determination among decision-makers is investigated by extending an algorithm taken from the technique for order preference by similarity-to-ideal solution. In this case, a pair of most compromising and least compromising solutions is derived from individual judgments of decision-makers and then, these solutions are applied as the bases for determining the magnitude of individual alignment with the group opinion by using a closeness coefficient approach. Determining the weights of decision-makers, the group decision-making problem is then solved. Application of the proposed method is illustrated by a numerical example for the selection of a maintenance strategy
Metadata only
Evolving a linear programming technique for MAGDM problems with interval valued intuitionistic fuzzy information
(Elsevier, 2015-08-04) Razavi Hajiagha, S.H.; Amoozad Mahdiraji, Hannan; Hashemi, S.S.; Zavadskas, E.K.
It is believed that multi attribute decision making problem is an ill-defined and unstructured problem. This difficulty intensifies while considering the uncertainty of decision makers’ information about the problem. In recent years, interval valued intuitionistic fuzzy sets (hereafter IVIFs) as a generalization of ordinal fuzzy sets, became a well-known and widely applied framework for dealing with uncertainty of decision making problems. However, the mathematical programming aspects of interval valued intuitionistic fuzzy sets besides their applications in decision making problems are neglected. To reinforce the mathematical programming approach in IVIF environment, an IVIF multi attribute group decision making problem is formulated as a linear programming model. Using a variable transformation and the notion of aggregation operators, the proposed model is transformed into an equivalent linear programming model solvable by common approaches. Application of the proposed method is represented in a group decision making problem and the results are compared with similar methods, proving the compatibility of the proposed method with previous ones. The solid and understandable logic with computational easiness are the main advantages of the proposed method. Solving interval valued intuitionistic fuzzy linear programming problems can be applied lucratively in other problems being formulated in this context.
Metadata only
Fuzzy C-Means based Data Envelopment Analysis for Mitigating the Impact of Units' Heterogeneity
(Emerald, 2016-03-07) Razavi Hajiagha, S.H.; Hashemi, S.S.; Amoozad Mahdiraji, Hannan
Purpose Data envelopment analysis (DEA) is a non-parametric model that is developed for evaluating the relative efficiency of a set of homogeneous decision-making units that each unit transforms multiple inputs into multiple outputs. However, usually the decision-making units are not completely similar. The purpose of this paper is to propose an algorithm for DEA applications when considered DMUs are non-homogeneous. Design/methodology/approach To reach this aim, an algorithm is designed to mitigate the impact of heterogeneity on efficiency evaluation. Using fuzzy C-means algorithm, a fuzzy clustering is obtained for DMUs based on their inputs and outputs. Then, the fuzzy C-means based DEA approach is used for finding the efficiency of DMUs in different clusters. Finally, the different efficiencies of each DMU are aggregated based on the membership values of DMUs in clusters. Findings Heterogeneity causes some positive impact on some DMUs while it has negative impact on other ones. The proposed method mitigates this undesirable impact and a different distribution of efficiency score is obtained that neglects this unintended impacts. Research limitations/implications The proposed method can be applied in DEA applications with a large number of DMUs in different situations, where some of them enjoyed the good environmental conditions, while others suffered from bad conditions. Therefore, a better assessment of real performance can be obtained. Originality/value The paper proposed a hybrid algorithm combination of fuzzy C-means clustering method with classic DEA models for the first time.
Open Access
A fuzzy data envelopment analysis approach based on parametric programming
(2013) Razavi Hajiagha, S.H.; Amoozad Mahdiraji, Hannan; Hashemi, S.S.; Zavadskas, E.K.
In this paper, a fuzzy version of original data envelopment models, CCR and BCC, is extended and its solution approach is developed. The basic idea of the proposed method is to transform the original DEA model to an equivalent linear parametric programming model, applying the notion of α-cuts. Then, a bi-objective model is constructed which its solution has determined the optimal range of decision making units efficiency. The proposed method can be used both for symmetric and asymmetric fuzzy numbers, while the feasibility of its solution for the original problem is guaranteed. The application of the proposed method is examined in two numerical examples and its results are compared with two current models of fuzzy DEA.
Metadata only
Fuzzy multi-objective linear programming based on compromise VIKOR method
(2014-05-16) Razavi Hajiagha, S.H.; Amoozad Mahdiraji, Hannan; Hashemi, S.S.; Zavadskas, E.K.
Real-world decision-making problems often consist in considering multiple and antithetic objectives. Therefore, multi-objective decision making (MODM) is a practical framework in implicational areas. In this paper, a fuzzy MODM problem is considered, where all of its parameters are defined fuzzily, and a solution inspired by multi-attribute VIKOR method is proposed. The proposed method tries to find fuzzy efficient solution for a problem by minimizing its combinational distance from an ideal and anti-ideal solution. This method can reveal the efficient frontier of the problem. Applicability of the proposed method is shown in an illustrative example and its application is summarized in an investment problem. Both examples show applicability of the proposed method.
Metadata only
A hybrid model of fuzzy goal programming and grey numbers in continuous project time, cost, and quality tradeoff
(Springer, 2013-11-20) Razavi Hajiagha, S.H.; Amoozad Mahdiraji, Hannan; Hashemi, S.S.
The purpose of this paper is to develop current mathematical models of cost, time, and quality tradeoffs in conditions that parameters of project activities are estimated uncertainly by grey numbers. In some projects like construction projects, activities can be done within a much shorter time by increasing in the resources, while project's cost may rise at the same time. In such situations, managers are usually required to determine the best combination of cost, time, and quality parameters of the activities, although their information regarding these parameters is limited and rather incomplete. The greyness of these parameters in the proposed method can aid managers to deal with these conditions. The most important aspect of the proposed model is that it considers uncertainty of the project planning data in the form of grey numbers. A combination of fuzzy goal programming and grey linear programming is also developed to solve the proposed model. Finally, this model will provide the managers with a stronger ability to face with uncertainty in project management and planning. The application of this model is examined in a numerical example. As its major finding, the model determines an optimal range in which the project managers can respond to intrinsic changes that may occur in the parameters during a project.
Open Access
An Integer Grey Goal Programming For Project Time, Cost and Quality Trade-Off
(2015) Razavi Hajiagha, S.H.; Akrami, H.; Hashemi, S.S.; Amoozad Mahdiraji, Hannan
Project management (PM) is one of the prominent fields in business and industry. Every task of an organization can be imagined as a project, being a coordinated set of activities toward a common goal. One important aspect of PM is analysing the information related to the optimum balance among the project’s objectives. Each project is a combination of different activities, being connected to each other and having several success criteria, among which the time, cost and quality of the project completion are more significant, due to their significant effect on obtained results. Accordingly, the time might lead to delay and penalty which means more cost; and cost may be underestimated than real required funds. They both will lead to failure in project management. On the other hand, quality is the final key which confirms the success. The aim of a time-cost-quality trade-off problem (TCQTP) is to select a set of activities and an appropriate execution mode for each activity; the cost and time of the project is minimized while the project quality is maximized. The purpose of this paper is to present a model for TCQTP in which these parameters are approximated by grey numbers. Since there are various modes to accomplish each activity, the trade-off problem is formulated based upon a multi-objective integer grey programming model. Afterwards, a goal programming- based approach is designed to solve this model. The model's results provide a framework for the project manager to manage his/ her project successfully, in acceptable time, with the lowest cost and the highest quality. The main originality of the proposed model is the approximation of time, cost and quality parameters of activities mode with grey numbers and the development of a two phase goal programming- based approach to solve this problem. Ultimately, the proposed model is applied in two different cases and results are illustrated to clarify the outstanding capabilities of the model
Open Access
An interval multi objective critical path method considering time, cost, quality and risk
(2016) Amoozad Mahdiraji, Hannan; Razavi Hajiagha, S.H.; Hashemi, S.S.; Zavadskas, E.K.
Metadata only
MAXIMIZING AND MINIMIZING SETS IN SOLVING FUZZY LINEAR PROGRAMMING
(2014) Razavi Hajiagha, S.H.; Amoozad Mahdiraji, Hannan; Zavadskas, E.K.; Hashemi, S.S.
Metadata only
Multi-period data envelopment analysis based on Chebyshev inequality bounds
(Elsevier, 2015) Razavi Hajiagha, S.H.; Hashemi, S.S.; Amoozad Mahdiraji, Hannan; Azaddel, J.
Data envelopment analysis is a cross-sectional approach to evaluate the relative efficiency of a set of homogeneous units in a single time point; nonetheless, organizational units have been performing continuously over a period of time; hence, their performances are considered within this period. Cumulating inputs and outputs over the time periods provide an unnecessary compensating impact, making the efficiency appraisal unrealistic. To avoid this negative impact of data accumulation, a two-stage approach on the basis of Chebyshev inequality bounds is proposed to find interval efficiency of decision making units (henceforth DMUs). The proposed method is applied in a real case encompassing 115 bank branches over 6 periods of time. This application indicated the significant cautious approach of the proposed method in multi-period data envelopment analysis (hereafter DEA).
Open Access
Multi‐objective linear programming with interval coefficients
(Emerald, 2013-03-22) Razavi Hajiagha, S.H.; Amoozad Mahdiraji, Hannan; Hashemi, S.S.
Purpose The purpose of this paper is to extend a methodology for solving multi‐objective linear programming (MOLP) problems, when the objective functions and constraints coefficients are stated as interval numbers. Design/methodology/approach The approach proposed in this paper for the considered problem is based on the maximization of the sum of membership degrees which are defined for each objective of multi objective problem. These membership degrees are constructed based on the deviation from optimal solutions of individual objectives. Then, the final model based on membership degrees is itself an interval linear programming which can be solved by current methods. Findings The efficiency of the solutions obtained by the proposed method is proved. It is shown that the obtained solution by the proposed method for an interval multi objective problem is Pareto optimal. Research limitations/implications The proposed method can be used in modeling and analyzing of uncertain systems which are modeled in the context of multi objective problems and in which required information is ill defined. Originality/value The paper proposed a novel and well‐defined algorithm to solve the considered problem.
Metadata only
A Novel Common Set of Weights Method for Multi-Period Efficiency Measurement using Mean-Variance Criteria
(Elsevier, 2018-07-24) Razavi Hajiagha, S.H.; Amoozad Mahdiraji, Hannan; Tavana, M.; Hashemi, S.S.
Data envelopment analysis (DEA) is a popular method for evaluating a set of homogeneous decision-making units (DMUs). One of the main shortcomings of DEA is the weights flexibility where each unit can take its desirable weights. Several methods have been developed for finding a common set of weights (CSWs) and overcoming this drawback. The CSWs methods are used to evaluate the relative efficiency of the DMUs in a single time-period. However, single period DEA models cannot handle organizational units performing in a continuum of time. We propose a novel method for determining the CSWs in a multi-period DEA. Initially, the CSWs problem is formulated as a multi-objective fractional programming problem. Subsequently, a multi-period form of the problem is formulated and the mean efficiency of the DMUs is maximized while their efficiency variances is minimized. A fuzzy set-based approach is used to solve the multi-period CSWs problem. We present a real-world case study to demonstrate applicability and exhibit the efficacy of the proposed method. The results indicate a significant improvement in the discrimination power of the proposed multi-period method.
Open Access
Total Ambient based on Orthogonal Vertices (TAOV) as a Novel Method of Multi-Criteria Decision Aid
(2018) Razavi Hajiagha, S.H; Amoozad Mahdiraji, Hannan; Hashemi, S.S.
Multi criteria decision aid (MCDA) deals with the problem of evaluating a set of finite alternatives regard to a set of finite criteria. A remarkable volume of qualitative and quantitative researches are done on decision making methods and situations, indicating its important role for managers at different organizational levels. These types of problems are applied in many different fields of human life. A challenging feature of these problems is non-existence of an optimal solution due to considering multiple criteria and the proposed methods seeking to find a satisfactory solution called efficient of Pareto-optimal. In consideration of MCDA problem, in this paper a new method is proposed for solving DM problems, consisting three fundamental steps of initialization, orthogonalization, and comparison. Thus, a new MCDA method called total area based on orthogonal vectors (TAOV) is introduced. This method is constructed on orthogonality of decision criteria. Application of TAOV method is illustrated in a decision problem and its performance is evaluated regard to other MCDA methods. Furthermore, its features are explained around the features of a desirable MCDA method. The obtained results indicate that the TAOV method can be considered as an acceptable method of handling multi-criteria decision making problems.

Browsing by Author "Hashemi, S.S."

Results Per Page

Sort Options