Papers by Parviz Mohsenpour
Arash Method (AM) is a new technique in Data Envelopment Analysis (DEA), which estimates the perf... more Arash Method (AM) is a new technique in Data Envelopment Analysis (DEA), which estimates the performance of Decision Making Units (DMUs) with flexible linear programming based on Additive DEA model (ADD). It is simultaneously able to discriminate technically efficient DMUs and/or inefficient ones without using statistical techniques, super-efficiency methods or requiring additional information in the case of weight restrictions. It simultaneously benchmarks both inefficient and technically efficient DMUs. AM is also able to measure the cost-efficiency of DMUs when cost information is available. It can be extended as a non-linear programming to have all the properties of linear AM and all capabilities of the Slack Based Measure (SBM) model. A practical definition based on AM score not only can find the best technically efficient DMUs, where small errors are introduced in their input values even if data are accurate, but it also provides an assurance that “small” errors in the measurement of input quantities did not result in “large” errors in the calculation of the efficiency index, which prompted introducing the axioms of continuity. This study clearly discusses about the capabilities of AM in comparison with most of previous DEA models with some numerical examples.
Usually in many applications some of inputs or outputs data may characteristically be integer val... more Usually in many applications some of inputs or outputs data may characteristically be integer values such as the number of students, hospitals and vehicles. However, the traditional data envelopment analysis (DEA) models would project a decision making unit (DMU) onto targets that generally do not respect such type of integrality constraints. There are some methods in DEA to assess the performance of those DMUs with integer-valued data. This study surveys the previous Mixed Integer linear programming (MILP) and illustrates the flaw of them with some counter examples. The study improves the previous MILP models and characterizes its capabilities with a numerical example. The simulations have been also performed with Lingo11 win64 software.
Islamic Republic of Iran has 8 international airports. This paper reports the performance evaluat... more Islamic Republic of Iran has 8 international airports. This paper reports the performance evaluation of these airports in the end of forth development plan of Iran in 2009 by applying Kourosh and Arash Model (KAM) in Data Envelopment Analysis (DEA). The area of airport, apron, terminal and runway are considered as inputs and the number of flights, the number of passengers and cargo are three selected outputs for each airport. Several scenarios are considered to rank and benchmark these airports without concerning about the number of airports. In other words, the scenarios are when inputs/outputs are controllable, when some of them are non-controllable and when the number of flights and passengers are restricted to the set of integer numbers and so on while the number of inputs and outputs are approximately the same as the number of airports. The results of these scenarios not only show the robustness of KAM to assess the performance evaluation of Decision Making Units (DMUs), but they also suggest the best international airports of Iran in 2009 as well as rank and benchmark them for each scenario.
Arash Method (AM) was proposed to measure the instabilities of technically efficient Decision Mak... more Arash Method (AM) was proposed to measure the instabilities of technically efficient Decision Making Units (DMUs) where very small errors are introduced in the input values. In this study, the instabilities of technically efficient DMUs are measured when very small errors are defined in the output values. The method is able to measure the revenue efficiency and has the advantages of AM in comparison with Slacked Based Measure model (SBM). Indeed, the model not only has all SBM properties, but also similar to AM it is appropriately able to arrange both technically efficient and inefficient DMUs.
Envelopment Analysis (DEA). The area of airport, apron, terminal and runway are considered as inp... more Envelopment Analysis (DEA). The area of airport, apron, terminal and runway are considered as inputs and the number of flights, the number of passengers and cargo are three selected outputs for each airport. Several scenarios are considered to rank and benchmark these airports without concerning about the number of airports. In other words, the scenarios are when inputs/outputs are controllable, when some of them are non-controllable and when the number of flights and passengers are restricted to the set of integer numbers and so on while the number of inputs and outputs are approximately the same as the number of airports. The results of these scenarios not only show the robustness of KAM to assess the performance evaluation of Decision Making Units (DMUs), but they also suggest the best international airports of Iran in 2009 as well as rank and benchmark them for each scenario.
Arash Method (AM) was proposed to measure the instabilities of technically efficient Decision Mak... more Arash Method (AM) was proposed to measure the instabilities of technically efficient Decision Making Units (DMUs) where very small errors are introduced in the input values. In this study, the instabilities of technically efficient DMUs are measured when very small errors are defined in the output values. The method is able to measure the revenue efficiency and has the advantages of AM in comparison with Slacked Based Measure model (SBM). Indeed, the model not only has all SBM properties, but also similar to AM it is appropriately able to arrange both technically efficient and inefficient DMUs.
Usually in many applications some of inputs or outputs data may characteristically be integer val... more Usually in many applications some of inputs or outputs data may characteristically be integer values such as the number of students, hospitals and vehicles. However, the traditional Data Envelopment Analysis (DEA) models would project a Decision Making Unit (DMU) onto targets that generally do not respect such type of integrality constraints. There are some methods in DEA to assess the performance of DMUs inclusive integer-valued data. This study surveys the previous Mixed Integer Linear Programming (MILP) and illustrates the flaw of them with some counter examples. The study improves the previous MILP models and characterizes its capabilities with a numerical example. The simulations have been also performed with Lingo11/win64 software.
Arash Method (AM) is a new technique in Data Envelopment Analysis (DEA), which estimates the perf... more Arash Method (AM) is a new technique in Data Envelopment Analysis (DEA), which estimates the performance of Decision Making Units (DMUs) with flexible linear programming based on Additive DEA model (ADD). It is simultaneously able to discriminate technically efficient DMUs and/or inefficient ones without using statistical techniques, super-efficiency methods or requiring additional information in the case of weight restrictions. It simultaneously benchmarks both inefficient and technically efficient DMUs. AM is also able to measure the cost-efficiency of DMUs when cost information is available. It can be extended as a non-linear programming to have all the properties of linear AM and all capabilities of the Slack Based Measure (SBM) model. A practical definition based on AM score not only can find the best technically efficient DMUs, where small errors are introduced in their input values even if data are accurate, but it also provides an assurance that "small" errors in the measurement of input quantities did not result in "large" errors in the calculation of the efficiency index, which prompted introducing the axioms of continuity. This study clearly discusses about the capabilities of AM in comparison with most of previous DEA models with some numerical examples.
Business operations can be more efficient by measuring the performance evaluation and estimating ... more Business operations can be more efficient by measuring the performance evaluation and estimating the production frontier as well as benchmarking and ranking Decision Making Units (DMUs). Data Envelopment Analysis (DEA) is a non-parametric technique to calculate these assessments. This paper introduces a new robust technique for approximating the S-shape empirically frontier while simultaneously benchmarking and ranking DMUs. Firstly, the main foundations of the new technique are illustrated with clear examples followed by depicting its properties and capabilities. A numerical example is also illustrated to show the advantages of the method for measuring the performance evaluation of DMUs. It is discussed how small errors in inputs and outputs may change the efficiency scores of DMUs significantly as well as benchmark and rank technically efficient and inefficient DMUs at the same time. The results represent whether a DMU has a good efficient combination of its data or how a DMU can regulate its inputs and outputs to improve its efficiency in response to small errors in the data. The simulations are performed with Microsoft Excel Solver as it required simple linear programming.
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Papers by Parviz Mohsenpour