Improving the performance of a medical imaging center through simulation and fuzzy DEA

2020 ◽  
pp. 2050059
Author(s):  
F. Gholami Golsefid ◽  
B. Daneshian ◽  
M. Rostamy-Malkhalifeh
Keyword(s):  
Medical Imaging ◽  
The Other ◽  
Data Envelopment ◽  
Imaging Center ◽  
Operational Technique ◽  
Decision Making Unit ◽  
Ranking Model ◽  
Simulation Results ◽  
Fuzzy Dea ◽  
Operational Methods

Given that various operational methods can be considered for a system, applying changes to study the results and determine the best operational technique is costly and disrupts the system. Thus, to analyze and evaluate the outcomes of employing different operational methods, simulation is utilized. In this study, to improve the performance of a medical imaging center (MIC), first, this center was simulated and then, different scenarios were defined and simulated. Subsequently, using the simulation results and for evaluating the scenarios through Data Envelopment Analysis (DEA), each scenario was considered as a decision making unit (DMU). Since simulation results of each scenario are uncertain and differ for different iterations, a method was utilized capable of using the results of all iterations. On the other hand, indexes such as satisfaction, patient’s appropriate waiting, helpful servicing with the least number nurses and the maximum number services that have fuzzy nature, are important factors for MIC. Therefore, using the simulation results and considering the system manager’s idea, a method was proposed for determining the fuzzy values of these indexes. Next, a ranking model and an algorithm were proposed for determining a unique ranking and introducing the best scenario to improve the performance of MIC.

scholarly journals A Full Ranking for Decision Making Units Using Ideal and Anti-Ideal Points in DEA

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
A. Barzegarinegad ◽  
G. Jahanshahloo ◽  
M. Rostamy-Malkhalifeh
Keyword(s):  
Decision Making ◽  
Real Data ◽  
The Other ◽  
Data Envelopment ◽  
Production Possibility ◽  
Decision Making Unit ◽  
Common Set Of Weights ◽  
Production Possibility Set ◽  
Ideal Points ◽  
Decision Making Units

We propose a procedure for ranking decision making units in data envelopment analysis, based on ideal and anti-ideal points in the production possibility set. Moreover, a model has been introduced to compute the performance of a decision making unit for these two points through using common set of weights. One of the best privileges of this method is that we can make ranking for all decision making units by solving only three programs, and also solving these programs is not related to numbers of decision making units. One of the other advantages of this procedure is to rank all the extreme and nonextreme efficient decision making units. In other words, the suggested ranking method tends to seek a set of common weights for all units to make them fully ranked. Finally, it was applied for different sets holding real data, and then it can be compared with other procedures.

Generalized Fuzzy Sample DEA Model and its Application in the Evaluation of Projects

2011 ◽  
Vol 63-64 ◽  
pp. 407-411
Author(s):  
Ren Mu ◽  
Zhan Xin Ma ◽  
Wei Cui ◽  
Yun Morigen Wu
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Input Output ◽  
Output Data ◽  
Dea Model ◽  
Decision Making Unit ◽  
Fuzzy Input ◽  
Fuzzy Dea

Evaluating the performance of activities or organizations by traditional data envelopment analysis model requires crisp input/output data. However, in real-world problems inputs and outputs are often with some fuzziness. To evaluate DMU with fuzzy input/output data, researchers provided fuzzy data envelopment analysis (FDEA) model and proposed related evaluating method. But up to now, we still cannot evaluate a fuzzy sample decision making unit (SDMU) for FDEA model. So this paper proposes a generalized fuzzy DEA model which can evaluate a sample decision making unit and a numerical experiment is used to illustrate this model.

Input/output weight restrictions, CSOI constraint and efficiency improvement

2016 ◽  
Vol 23 (7) ◽  
pp. 2080-2091
Author(s):  
Sanjeet Singh ◽  
Surya Majumdar
Keyword(s):  
Decision Maker ◽  
Carbon Dioxide Emissions ◽  
The Other ◽  
Data Envelopment ◽  
Efficiency Improvement ◽  
Input Output ◽  
Weight Restrictions ◽  
Content Type ◽  
Decision Making Unit ◽  
Dea Models

Purpose The purpose of this paper is to develop data envelopment analysis (DEA) models and algorithms for efficiency improvement when the inputs and output weights are restricted and there is fixed availability of inputs in the system. Design/methodology/approach Limitation on availability of inputs is represented in the form of constant sum of inputs (CSOI) constraint. The amount of excess input of an inefficient decision-making unit (DMU) is redistributed among other DMUs in such a way so that there is no reduction in their efficiency. DEA models have been developed to design the optimum strategy to reallocate the excess input. Findings The authors have developed the method for reallocating the excess input among DMUs while under CSOI constraint and parameter weight restrictions. It has been shown that in this work to improve the efficiency of an inefficient DMU one needs the cooperation of selected few DMUs. The working of the models and results have been shown through a case study on carbon dioxide emissions of 32 countries. Research limitations/implications The limitation of the study is that only one DMU can expect to benefit from the application of these methods at any given time. Practical implications Results of the paper are useful in situations when decision maker is exploring the possibility of transferring the excess resources from underperforming DMUs to the other DMUs to improve the performance. Originality/value This strategy of reallocation of excess input will be very useful in situations when decision maker is exploring the possibility of transferring the excess resources from underperforming DMUs to the other DMUs to improve the performance. Unlike the existing works on efficiency improvement under CSOI, this work seeks to address the issue of efficiency improvement when the input/output parameter weights are also restricted.

scholarly journals Dynamic Energy Efficiency, Energy Decoupling Rate, and Decarbonization: Evidence from ASEAN+6

SAGE Open ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 215824402110472
Author(s):  
Chiang-Ping Chen ◽  
Ming-Chung Chang ◽  
Wei-Che Tsai
Keyword(s):  
Decision Making ◽  
Energy Efficiency ◽  
Data Envelopment Analysis ◽  
Behavior Change ◽  
The Other ◽  
Data Envelopment ◽  
Dynamic Efficiency ◽  
Energy Usage ◽  
Proposed Model ◽  
Decision Making Unit

Improving energy efficiency is widely identified as shifting energy usage to an optimal status in order to ultimately strengthen a country’s competitiveness and development, and indeed this is of particular relevance to the Association of Southeast Asian Nations plus Six’ (ASEAN+6). The traditional data envelopment analysis (DEA) approach has extensively been employed for estimating energy efficiency, but it does not properly utilize the weight in the DEA model to probe the behavior change of a decision making unit (DMU). This research therefore applies a progressive time-weighted dynamic efficiency model (PTDEM) to estimate the energy efficiency of ASEAN+6 and discusses the issues concerning their energy decoupling rates and decarbonization. The proposed model herein fully considers a DMU’s behavior change by estimating its energy efficiency. Empirical results reveal that: (i) improvements in energy efficiency within ASEAN are greater than in the other six countries; (ii) members of ASEAN still have more room for improvement than the other six countries with regard to achieving the standard ratio of the energy decoupling rate; and (iii) there is no evidence of convergence to decarbonization within ASEAN+6.

A generalized fuzzy cost efficiency model

2020 ◽  
Vol 54 (6) ◽  
pp. 1775-1791
Author(s):  
Nazila Aghayi ◽  
Samira Salehpour
Keyword(s):  
Cost Efficiency ◽  
Minimum Cost ◽  
Extensive Literature ◽  
Data Envelopment ◽  
Fuzzy Environment ◽  
Decision Making Unit ◽  
Production Possibility Set ◽  
Fuzzy Cost ◽  
The Cost ◽  
Generalized Cost

The concept of cost efficiency has become tremendously popular in data envelopment analysis (DEA) as it serves to assess a decision-making unit (DMU) in terms of producing minimum-cost outputs. A large variety of precise and imprecise models have been put forward to measure cost efficiency for the DMUs which have a role in constructing the production possibility set; yet, there’s not an extensive literature on the cost efficiency (CE) measurement for sample DMUs (SDMUs). In an effort to remedy the shortcomings of current models, herein is introduced a generalized cost efficiency model that is capable of operating in a fuzzy environment-involving different types of fuzzy numbers-while preserving the Farrell’s decomposition of cost efficiency. Moreover, to the best of our knowledge, the present paper is the first to measure cost efficiency by using vectors. Ultimately, a useful example is provided to confirm the applicability of the proposed methods.

Relative Efficiency of Decision Making Units Producing Both Desirable and Undesirable Outputs: A Case of Textile Processing Units in Pakistan.

2011 ◽  
Vol 50 (4II) ◽  
pp. 685-698
Author(s):  
Samina Khalil
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Relative Efficiency ◽  
Value Added ◽  
Data Envelopment ◽  
Undesirable Outputs ◽  
Textile Processing ◽  
Decision Making Unit ◽  
Desirable And Undesirable Outputs ◽  
Decision Making Units

This paper aims at measuring the relative efficiency of the most polluting industry in terms of water pollution in Pakistan. The textile processing is country‘s leading sub sector in textile manufacturing with regard to value added production, export, employment, and foreign exchange earnings. The data envelopment analysis technique is employed to estimate the relative efficiency of decision making units that uses several inputs to produce desirable and undesirable outputs. The efficiency scores of all manufacturing units exhibit the environmental consciousness of few producers is which may be due to state regulations to control pollution but overall the situation is far from satisfactory. Effective measures and instruments are still needed to check the rising pollution levels in water resources discharged by textile processing industry of the country. JEL classification: L67, Q53 Keywords: Data Envelopment Analysis (DEA), Decision Making Unit (DMU), Relative Efficiency, Undesirable Output

An Intuitionistic Fuzzy Based Novel Approach to CPU Scheduler

2020 ◽  
Vol 16 (4) ◽  
pp. 316-328
Author(s):  
Supriya Raheja
Keyword(s):  
Fuzzy Inference ◽  
The Other ◽  
Simulation Environment ◽  
Inference System ◽  
Intuitionistic Fuzzy ◽  
Novel Approach ◽  
Continuous Feedback ◽  
Simulation Results ◽  
Effectiveness And Efficiency ◽  
Unique Capability

Background: The extension of CPU schedulers with fuzzy has been ascertained better because of its unique capability of handling imprecise information. Though, other generalized forms of fuzzy can be used which can further extend the performance of the scheduler. Objectives: This paper introduces a novel approach to design an intuitionistic fuzzy inference system for CPU scheduler. Methods: The proposed inference system is implemented with a priority scheduler. The proposed scheduler has the ability to dynamically handle the impreciseness of both priority and estimated execution time. It also makes the system adaptive based on the continuous feedback. The proposed scheduler is also capable enough to schedule the tasks according to dynamically generated priority. To demonstrate the performance of proposed scheduler, a simulation environment has been implemented and the performance of proposed scheduler is compared with the other three baseline schedulers (conventional priority scheduler, fuzzy based priority scheduler and vague based priority scheduler). Results: Proposed scheduler is also compared with the shortest job first CPU scheduler as it is known to be an optimized solution for the schedulers. Conclusion: Simulation results prove the effectiveness and efficiency of intuitionistic fuzzy based priority scheduler. Moreover, it provides optimised results as its results are comparable to the results of shortest job first.

A simulator to improve waiting times at a Medical Imaging Center

2008 ◽  
Author(s):  
Francisco J. Ramis ◽  
Felipe Baesler ◽  
Edgar Berho ◽  
Liliana Neriz ◽  
Jose A. Sepulveda
Keyword(s):  
Medical Imaging ◽  
Waiting Times ◽  
Imaging Center

A Multiregion Model with Capital Accumulation and Endogenous Amenities

2007 ◽  
Vol 39 (9) ◽  
pp. 2248-2270 ◽  
Author(s):  
Wei-Bin Zhang
Keyword(s):  
Capital Accumulation ◽  
Comparative Statics ◽  
The Other ◽  
High Rate ◽  
Unique Equilibrium ◽  
Economic Activities ◽  
Technological Differences ◽  
National Output ◽  
Simulation Results ◽  
Wage Disparities

The author develops a multiregional growth model with endogenous amenity and capital accumulation for any number of regions. The simulation results demonstrate that the national dynamics have a unique equilibrium. Comparative statics analysis shows that, if environmental improvement occurs in the technologically advanced (less advanced) region, the national output rises (falls). As a region improves its technology, the other two regions' aggregated output levels fall—not only in relative, but also in absolute, terms. This implies that if any region has a high rate of technological change and the other regions remain technologically stationary, then economic activities will tend to be concentrated in the technologically advancing region. It is also shown that technological differences appear to play only a small role in accounting for spatial wage disparities and endowments.

Simulation on Effect of Five Kinds of Belt Structures on Tire Performance

2012 ◽  
Vol 501 ◽  
pp. 151-155
Author(s):  
Yong Liu ◽  
Ge Zhang ◽  
Hua Yan ◽  
Yu Mei Ding ◽  
Wei Min Yang
Keyword(s):  
The Other ◽  
Molding Process ◽  
Simulation Results ◽  
Better Than

In this article, three kinds of belt named B, C and D type are invented, then their main performance are compared with the other two kinds of belt structures introduced in previous papers. Simulation results showed that B and D-type belts are better than the other three. Comparatively the latter needs less material, its molding process is easier, and the tire body is lighter than B type tire, so in general it can be considered that D-type belt is the best among the five kinds of belt structures.

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