2021
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Evaluating the Congestion Effect in the TwoStage Structures by NDEA Models
Evaluating the Congestion Effect in the TwoStage Structures by NDEA Models
http://www.jmor.ir/article_240075.html
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Congestion is an important issue in economics and data envelopment analysis (DEA). It occurs when one or more outputs can be increased by reducing one or more inputs, without worsening any other input or output. In recent years, there have been various studies dealt with twostage production systems by DEA models. These systems consume some inputs in their first stage to produce some intermediate outputs which are used as the inputs of the second stage in producing final output. So far, it is not much attention to the existence of the congestion effect in these structures. In this article, we have focused on a congestion effect on the twostage structures via network DEA models. In addition, this study proposes a new method for measuring congestion in divisions of the network. This model can evaluate congestion in the network structure and identify that which factors cause of the congestion
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Congestion is an important issue in economics and data envelopment analysis (DEA). It occurs when one or more outputs can be increased by reducing one or more inputs, without worsening any other input or output. In recent years, there have been various studies dealt with twostage production systems by DEA models. These systems consume some inputs in their first stage to produce some intermediate outputs which are used as the inputs of the second stage in producing final output. So far, it is not much attention to the existence of the congestion effect in these structures. In this article, we have focused on a congestion effect on the twostage structures via network DEA models. In addition, this study proposes a new method for measuring congestion in divisions of the network. This model can evaluate congestion in the network structure and identify that which factors cause of the congestion
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مائده
غلام زاده
GholamAzad
Maedeh
Iran
m.gholamazad@azaruniv.ac.ir
جعفر
پورمحمد
Pourmahmoud
Jafar
Iran
pourmahmoud@azaruniv.ac.ir
Congestion
Division
Twostage structure
DEA
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The Position of Multiobjective Programming Methods in Fuzzy Data Envelopment Analysis
The Position of Multiobjective Programming Methods in Fuzzy Data Envelopment Analysis
http://www.jmor.ir/article_240081.html
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Traditional Data Envelopment Analysis (DEA) models evaluate the efficiency ofdecision making units (DMUs) with common crisp input and output data. However, the data in real applications are often imprecise or ambiguous. This paper transforms fuzzy fractional DEA model which is constructed using fuzzy arithmetic, into the conventional crisp model. This transformation is performed considering the goal programming that is one of the Multi Objective Programming (MOP) methods. Therefore, in this research the one linear programming model measures the fuzzy efficiencies of DMUs with fuzzy input and fuzzy output data
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Traditional Data Envelopment Analysis (DEA) models evaluate the efficiency ofdecision making units (DMUs) with common crisp input and output data. However, the data in real applications are often imprecise or ambiguous. This paper transforms fuzzy fractional DEA model which is constructed using fuzzy arithmetic, into the conventional crisp model. This transformation is performed considering the goal programming that is one of the Multi Objective Programming (MOP) methods. Therefore, in this research the one linear programming model measures the fuzzy efficiencies of DMUs with fuzzy input and fuzzy output data
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پ
زمانی
Zamani
P
Iran
zamany2007@yahoo.com
م.م
شفیعی زاده
Shafiei Zadeh
M.M
Iran
mehdi_shafie_90@yahoo.com
Data Envelopment Analysis
Fuzzy input and fuzzy output data
Fuzzy efficiency
Multiobjective programming
Goal programming
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A random forest approach on Multiobjective flexible jobshop scheduling problem
A random forest approach on Multiobjective flexible jobshop scheduling problem
http://www.jmor.ir/article_246817.html
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The traditional jobshop scheduling problem (JSP) requires the allocation of N independent jobs on M machines. In most flexible jobshop scheduling problem assumptions that all machines are always available. But unexpected machine failure that is called the random machine break downs is not considered. So, the stability of schedules can be computed. In this paper, an inversed modelbased on random forest method in which a Gaussian process and variable importance random forest algorithm are used for mapping nondominated solutions from the objective space (PF) to the decision space (PS). Then this proposed method is applied on an FJSP with random machine breakdowns (RMBs) which the stability of the schedule is detected by the deviation of each job time preschedule and real schedule. The proposed algorithm has been tested on the benchmark test suite for flexible jobshop scheduling problem and has compared with IMMOEA and NSGAII and indicates that the proposed method is a competitive and promising approach.
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The traditional jobshop scheduling problem (JSP) requires the allocation of N independent jobs on M machines. In most flexible jobshop scheduling problem assumptions that all machines are always available. But unexpected machine failure that is called the random machine break downs is not considered. So, the stability of schedules can be computed. In this paper, an inversed modelbased on random forest method in which a Gaussian process and variable importance random forest algorithm are used for mapping nondominated solutions from the objective space (PF) to the decision space (PS). Then this proposed method is applied on an FJSP with random machine breakdowns (RMBs) which the stability of the schedule is detected by the deviation of each job time preschedule and real schedule. The proposed algorithm has been tested on the benchmark test suite for flexible jobshop scheduling problem and has compared with IMMOEA and NSGAII and indicates that the proposed method is a competitive and promising approach.
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Pezhman
Gholamnezhad
Faculty of Computer Engineering and Information Technology, Shahid Sattari University
Iran
pezhman.gholamnezhad@gmail.com
Flexible jobshop scheduling problem
stability
Random machine breakdowns
Random forest variable importance
Multiobjective optimization