Using DEA in conjunction with designs of experiments: an approach to assess simulated futures in the Afghan educational system

Marlin, Benjamin; Sohn, Hansuk

doi:10.1057/jos.2015.14

Cited by 3 publications

(4 citation statements)

References 21 publications

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“…Marlin and Sohn presented a hybrid analytical process that combined simulation, DOE, and DEA in the Afghan educational system. In this study, the importance of DEA indicators did not determine [17]. The DES, DOE, and DEA methods are considered as some suitable methods for evaluating the behavior of a system [12].…”

Section: Introductionmentioning

confidence: 94%

“…Previous research tried to relieve this weakness and use the benefits of simulation, DEA, and DOE methods simultaneously. The combinations of these methods have used to improve the performance of the PS in the automobile spare parts manufacturer [11] and evaluate the performance of the educational system [17].…”

Section: Insert Table 12 Herementioning

confidence: 99%

“…The model did not consider a proper method for designing and analyzing the scenarios of the simulation approach [16]. In the large scale simulation, a sophisticated computer experiment frequently requires permutation among hundreds or even thousands of input variables and takes a long time to run each excursion [17]. Thus, performance evaluation in PS can utilized through Optimization via Simulation (OVS), which is based on DES principles and considered as one of the most essential techniques.…”

Section: Introductionmentioning

confidence: 99%

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Simulation-Based Optimization using DEA and DOE in Production System

2021

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Production System (PS) is the process of planning, organizing, directing and controlling the tactical and strategic planning of the different components of the company, to transform inputs into finished products which must be effectively managed. Important parts of PS that always face major challenges in manufacturing systems include production strategy, resource allocation, logistics and production planning. Because of the importance of examining the various components of PS and evaluating its performance on key indicators of organization, it is necessary to evaluate the impact of any changes in these elements to the system prior to its creation. In this regard, the present study aimed to increasing the efficiency and determining the useful methods to evaluate and optimize the performance in different part of PS. To this end, an integrated Discrete-Event Simulation (DES), Design of Experiments (DOE), Data Envelopment Analysis (DEA), and Multi-Attribute Decision Making (MADM) models were implemented to analyze and optimize the real PS process. In the case study of the automobile manufacturing industry in Iran, the accurate analysis was applied to the proposed approach and its different aspects were considered as well. The results indicated that the proposed approach is a practical way for evaluating and optimizing the performance of different part of PS, compared to previous models and helps the manufacturing companies to make efficient decisions regarding increasing productivity while decreasing the essential problems.

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Section: Introductionmentioning

confidence: 94%

Section: Insert Table 12 Herementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Simulation-Based Optimization using DEA and DOE in Production System

2021

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“…Particularly in experimental design, the use of DEA is not new. Marlin and Sohn (2016) proposed a hybrid process that combines simulation, design of experiments, and DEA to study an educational system. Yang et al (2016) applied DEA and design of experiment concepts to evaluate the emission of water pollutants.…”

Section: Introductionmentioning

confidence: 99%

Factors affecting the performance of Pantaneiro horses

et al. 2018

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-This study aimed to assess the physical performance of Pantaneiro horses with and without equine infectious anemia (EIA) under functional conditions of cattle management. The horses were subjected to a performance test and split into two groups according to a completely randomized design: animals were chosen from populations testing positive and negative for EIA. Performance was measured as a function of a data envelopment analysis (DEA) model considering four outputs and one unitary input. The output measures were the distance achieved in the performance test, hematocrit as a weighted average over the test duration, respiratory rate as weighted average over the test duration, and the level of lactic acid at the test termination. Weights for the hematocrit and the respiratory rate output variables were determined by means of factor analysis. The performance score was a weighted average of the output variables with the weights defined by the averages of the optimum individual multipliers in the DEA analysis. Contextual variables of interest were age, horse weight, room temperature, and corporal temperature. Only groups and room temperature were statistically significant effects, as indicated by a bootstrap analysis. The performance of group positive for EIA is significantly lower than that of the group negative for EIA and room temperature has a negative effect.

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An agent-based model of school tracking, accountability, and segregation

Pensiero,

Brede

2024

Journal of Simulation

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Using DEA in conjunction with designs of experiments: an approach to assess simulated futures in the Afghan educational system

Cited by 3 publications

References 21 publications

Simulation-Based Optimization using DEA and DOE in Production System

Simulation-Based Optimization using DEA and DOE in Production System

Factors affecting the performance of Pantaneiro horses

An agent-based model of school tracking, accountability, and segregation

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