Gholam R. Amin

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Papers by Gholam R. Amin

A review of inverse data envelopment analysis: origins, development and future directions

IMA Journal of Management Mathematics

Data envelopment analysis (DEA) is a widely used mathematical programming approach for assessing ... more Data envelopment analysis (DEA) is a widely used mathematical programming approach for assessing the efficiency of decision-making units (DMUs) in various sectors. Inverse DEA is a post-DEA sensitivity analysis approach developed initially for solving resource allocation. The main objective of inverse DEA is to determine the optimal quantity of inputs and/or outputs for each DMU under input and/or output perturbation (s), which would allow them to reach a given efficiency target. Since the early 2000s, inverse DEA has been extended theoretically and applied successfully in different areas including banking, energy, education, sustainability and supply chain management. In recent years, research has demonstrated the potential of inverse DEA for solving novel inverse problems, such as estimating merger gains, minimizing production pollution, optimizing business partnerships and more. This paper provides a comprehensive survey of the latest theoretical and practical advancements in inv...

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A decision framework for cloud migration: A hybrid approach

IET Software

Advances in inverse data envelopment analysis: empowering performance assessment

IMA Journal of Management Mathematics

Comment on “The general form of 0–1 programming problem based on DNA computing, by Yin ZhiXiang et al.”

Biosystems, 2005

Reactivity of target compounds for chemical coal desulfurization. Quarterly technical report, September 1, 1993November 30, 1993

This project seeks to determine the identity of representative organosulfur compounds removed by ... more This project seeks to determine the identity of representative organosulfur compounds removed by coal desulfurization reactions. Demineralized coals from the Illinois Basin Coal Sample Program are solvent extracted and the extracts fractionated to separate and concentrate the organosulfur compounds for analysis by Gas Chromatography/Mass Spectroscopy. After the sulfur compounds are characterized, the parent extracts will be subjected to reactions previously

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DEA models for ratio data: Convexity consideration

Applied Mathematical Modelling, 2009

Data envelopment analysis (DEA) is defined based on observed units and by finding the distance of... more Data envelopment analysis (DEA) is defined based on observed units and by finding the distance of each unit to the border of estimated production possibility set (PPS). The convexity is one of the underlying assumptions of the PPS. This paper shows some difficulties of using standard DEA models in the presence of input-ratios and/or output-ratios. The paper defines a new convexity assumption when data includes a ratio variable. Then it proposes a series of modified DEA models which are capable to rectify this problem.

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Finding the most efficient DMUs in DEA: An improved integrated model

Computers & Industrial Engineering, 2007

In many applications of DEA finding the most efficient DMUs is desirable. This paper presents an ... more In many applications of DEA finding the most efficient DMUs is desirable. This paper presents an improved integrated DEA model in order to detect the most efficient DMUs. The proposed integrated DEA model does not use the trial and error method in the objective function. Also, it is able to find the most efficient DMUs without solving the model n times (one linear programming (LP) for each DMU) and therefore allows the user to get faster results. It is shown that the improved integrated DEA model is always feasible and capable to rank the most efficient one. To illustrate the model capability the proposed methodology is applied to a real data set consisting of the 19 facility layout alternatives.

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A note on an improved MCDM DEA model for technology selection

International Journal of Production Research, 2008

... Department of Computer Engineering, Islamic Azad University of South Tehran Branch, Tehran, I... more

Threshold value for the number of cells in group technology

The similarity coefficient methods are more flexible in incorporating manufacturing data into the... more The similarity coefficient methods are more flexible in incorporating manufacturing data into the machine cells formation process in group technology. When threshold value is applied it is impossible to consider the restriction of number of cells or pact family. This paper discusses how a function is defined on Similarity coefficients and generates a threshold value which specifies an upper band

An assurance interval for the non-Archimedean epsilon in DEA models

... SAEID MEHRABIAN, GHOLAM R. JAHANSHAHLOO, and MOHAMMAD R. ALIREZAEE Department of Mathematics,... more

Improving Efficiency Scores of Inefficient Units with Restricted Primary Resources

An important issue in Data Envelopment Analysis (DEA) is finding the efficiency scores of Decisio... more An important issue in Data Envelopment Analysis (DEA) is finding the efficiency scores of Decision Making Units (DMUs). For improving the efficiency scores of inefficient units, it is important to consider the primary resources fixed and restricted. In this paper, we propose a model to improve the efficiency scores of inefficient units with restricted primary resources. We also suggest the perturbation on primary resources in such a way that the efficiency scores of inefficient units improved and the efficient DMUs remain unchanged.

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A generalized sensitivity analysis DEA model

ABSTRACT Sensitivity analysis in DEA is used for improving the efficiency scores of inefficient D... more ABSTRACT Sensitivity analysis in DEA is used for improving the efficiency scores of inefficient DMUs for which the efficient units remain unchanged. This paper introduces a generalized sensitivity analysis DEA model by perturbation a given input (or output) for all efficient DMUs. A numerical example illustrates the usefulness of the new model.

A new DEA model for technology selection in the presence of ordinal data

ABSTRACT This paper suggests a data envelopment analysis (DEA) model for selecting the most effic... more ABSTRACT This paper suggests a data envelopment analysis (DEA) model for selecting the most efficient alternative in advanced manufacturing technology in the presence of both cardinal and ordinal data. The paper explains the problem of using an iterative method for finding the most efficient alternative and proposes a new DEA model without the need of solving a series of LPs. A numerical example illustrates the model, and an application in technology selection with multi-inputs/multi-outputs shows the usefulness of the proposed approach.

An efficient DEA method for ranking woven fabric defects in textile manufacturing

ABSTRACT This paper deals with the problem of ranking woven fabric defects (WFDs) observed in tex... more ABSTRACT This paper deals with the problem of ranking woven fabric defects (WFDs) observed in textile manufacturing using a data envelopment analysis (DEA) method. The paper shows that the optimal solutions of DEA models for decision-making units (DMUs) with multiple inputs can be found without the need of solving the corresponding models. The paper performs a mean–variance analysis for determining the most important statistical factors of WFDs in terms of multiple inputs. The paper also ranks the observed WFDs from the worst preferred using the suggested DEA formulation. The contribution of this study can be explained as follows. It introduces a new application for DEA method in textile manufacturing for ranking fabric defects. This is significant in defining rich project in reducing defects through prioritizing of quality specification of fabric defects by Six Sigma experts. Also, the result of this paper can be obtained using an efficient DEA method without the need of solving the corresponding DEA models for any sample size of fabric defects.

Comment on: The general form of 0-1 programming problem based on DNA computing, by Yin ZhiXiang et al

Erratum to? A polynomial-time algorithm for finding Formula Not Shown in DEA models?

With reference to the paper, Theorem 2 (p. 805) should be corrected as following: Theorem 2. The ... more With reference to the paper, Theorem 2 (p. 805) should be corrected as following: Theorem 2. The Epsilon algorithm runs in O(nq), where q = max{m, s}. Also the last two sentences given in the proof of Theorem 2 must be corrected by: Because the total number of operations is (1 + m + s)n and noting that m, s and n are three parameters of DEA observations, or the problem size, therefore the complexity of the algorithm is O(nq).

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Metasearch information fusion using linear programming

For a specific query merging the returned results from multiple search engines, in the form of a ... more For a specific query merging the returned results from multiple search engines, in the form of a metasearch aggregation, can provide significant improvement in the quality of relevant documents. This paper suggests a minimax linear programming (LP) formulation for fusion of multiple search engines results. The paper proposes a weighting method to include the importance weights of the underlying search engines. This is a two-phase approach which in the first phase a new method for computing the importance weights of the search engines is introduced and in the second stage a minimax LP model for finding relevant search engines results is formulated. To evaluate the retrieval effectiveness of the suggested method, the 50 queries of the 2002 TREC Web track were utilized and submitted to three popular Web search engines called Ask, Bing and Google. The returned results were aggregated using two exiting approaches, three high-performance commercial Web metasearch engines and our proposed technique. The efficiency of the generated lists was measured using TREC-Style Average Precision (TSAP). The new findings demonstrate that the suggested model improved the quality of merging considerably.

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Choosing the best Twenty20 cricket batsmen using ordered weighted averaging

ABSTRACT This paper provides a way to evaluate and choose the best Twenty20 (T20) cricket batsmen... more ABSTRACT This paper provides a way to evaluate and choose the best Twenty20 (T20) cricket batsmen using ordered weighted averaging (OWA) operator. The paper suggests an OWA evaluation method for a cricket batsman using multiple attributes related to the player&#39;s performance. A dataset consisting of ten important attributes for 24 T20 Indian Premier League 4 (IPL 4) cricket batsmen is used to choose the best players. Also, a comparison result shows the advantage of using the proposed OWA method. The proposed method in this paper can also be used for evaluation of T20 bowlers in turn in the selection of a T20 cricket team.

A new inverse DEA method for merging banks

This study suggests a novel application of Inverse Data Envelopment Analysis (InvDEA) in strategi... more This study suggests a novel application of Inverse Data Envelopment Analysis (InvDEA) in strategic decision making about mergers and acquisitions in banking. The conventional DEA assesses the efficiency of banks based on the information gathered about the quantities of inputs used to realize the observed level of outputs produced. The decision maker of a banking unit willing to merge/acquire another banking unit needs to decide about the inputs and/or outputs level if an efficiency target for the new banking unit is set. In this paper, a new InvDEA-based approach is developed to suggest the required level of the inputs and outputs for the merged bank to reach a predetermined efficiency target. This study illustrates the novelty of the proposed approach through the case of a bank considering merging with or acquiring one of its competitors to synergize and realize higher level of efficiency. A real data set of 42 banking units in Gulf Corporation Council countries is used to show the practicality of the proposed approach.

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A polynomial-time algorithm for finding< i> ε</i> in DEA models

Gholam R. Amin

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