Zobrazeno 1 - 10
of 60
pro vyhledávání: '"Reza Kazemi Matin"'
Publikováno v:
Operations Research and Decisions, Vol vol. 32, Iss no. 3, Pp 80-91 (2022)
Although Data Envelopment Analysis (DEA) assumes that inputs and outputs take non-negative real values, in some realworld cases, data are integer-valued. In some situations, rounding a fractional value to the closest integer can lead to a misleading
Externí odkaz:
https://doaj.org/article/ded34a8836d94178927c0dc8fbef02b1
Publikováno v:
Iranian Journal of Optimization, Vol 10, Iss 1, Pp 19-29 (2018)
In production theory, it is necessary to be capable of predicting the production func- tion’s long-run behaviors. Hereof, returns to scale is a helpful concept. Returns to scale describes the reaction of a production function to the proportionally
Externí odkaz:
https://doaj.org/article/b24156c71dd546df8399a730c465f2d5
Autor:
Roza Azizi, Reza Kazemi Matin
Publikováno v:
Journal of Optimization in Industrial Engineering, Vol 11, Iss 1, Pp 195-202 (2018)
Conventional data envelopment analysis (DEA) models are used to measure efficiency score of production systems when they are considered as black boxes and their internal relationship is ignored. This paper deals with a common special case of network
Externí odkaz:
https://doaj.org/article/6021f66f77534fa48634c1493d22ebcf
Autor:
Reza Kazemi Matin, Roza Azizi
Publikováno v:
Journal of Optimization in Industrial Engineering, Vol 9, Iss 20, Pp 103-109 (2016)
Traditional data envelopment analysis (DEA) models deal with measurement of relative efficiency of decision making units (DMUs) in which multiple-inputs consumed to produce multiple-outputs. One of the drawbacks of these models is neglecting internal
Externí odkaz:
https://doaj.org/article/125bf30f1ed44982b046d5f2a8e58ed9
Autor:
Reza Kazemi Matin, Roza Azizi
Publikováno v:
Journal of Optimization in Industrial Engineering, Vol 8, Iss 17, Pp 31-36 (2015)
In the classical data envelopment analysis (DEA) models, inputs and outputs are assumed as known variables, and these models cannot deal with unknown amounts of variables directly. In recent years, there are few researches on handling missing data. T
Externí odkaz:
https://doaj.org/article/399713314c5f4f3c9ae3e3efc1fe84ce
Autor:
Reza Kazemi Matin
Publikováno v:
Journal of Optimization in Industrial Engineering, Vol Volume 4, Iss 8, Pp 33-40 (2011)
Data Envelopment Analysis (DEA) has been widely studied in the literature since its inception with Charnes, Cooper and Rhodes work in 1978. The methodology behind the classical DEA method is to determine how much improvements in the outputs (inputs)
Externí odkaz:
https://doaj.org/article/eaf642ccb6274182bc55bcb582e9dd48
Autor:
Morteza Khodabin, Reza Kazemi Matin
Publikováno v:
Iranian Journal of Optimization, Vol 06, Iss 1, Pp 536-554 (2010)
In the use of peer group data to assess individual, typical or best practice performance, the effective detection of outliers is critical for achieving useful results. In these ‘‘deterministic’’ frontier models, statistical theory is now most
Externí odkaz:
https://doaj.org/article/059707bc8c2843618fb2283a9e5bc89d
Autor:
roza azizi, reza kazemi matin
Publikováno v:
Journal of Optimization in Industrial Engineering, Vol Volume 3, Iss Issue 5, Pp 67-71 (2010)
Data envelopment analysis (DEA) is a non-parametric approach for performance analysis of decision making units (DMUs) which uses a set of inputs to produce a set of outputs without the need to consider internal operations of each unit. In recent year
Externí odkaz:
https://doaj.org/article/31d78371a87d4f1daae33c13e721da68
Publikováno v:
Annals of Operations Research. 321:281-309
The utilization of meta-heuristics has been widespread in resolving optimization problems, with constant development of new and effective algorithms. Thisresearch presents the Garter Snake Optimization Algorithm (GSO), which ismotivated by the mating
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3fc5c82e3415919c8dc2747294508fb7
https://doi.org/10.21203/rs.3.rs-2899298/v1
https://doi.org/10.21203/rs.3.rs-2899298/v1