A Methodology for Optimization in Multistage Industrial Processes: A Pilot Study

Jarosz, P.; Kusiak, J.; Małecki, S.; Oprocha, Piotr; Sztangret, Łukasz; Wilkus, Marek

doi:10.1155/2015/182679

Cited by 8 publications

(3 citation statements)

References 9 publications

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“…Details of some researches in this field can be found in Despotis and Koronakos [3], Carayannis et al [4], Jarosz et al [5], and Gang et al [6]. The first DEA model, CCR, was proposed by Charnes et al [7] with assumption of constant-returns-to-scale.…”

Section: Introductionmentioning

confidence: 99%

The NDEA–MOP Model in the Presence of Negative Data Using Fuzzy Method

et al. 2017

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In this study, the multi-objective programming (MOP) method was used to solve network DEA (NDEA) models with assumption that, negative data is considered for the proposed NDEA model which consists of semi-negative and semi-positive input and output. At first, two stage and then k stage production models were formulated with consideration of negative data. In the multi-objective programming, two separate objective functions including the divisional efficiencies and the overall efficiency of the organization are modeled. In comparison to conventional DEA with negative data, the advantage of the proposed NDEA 2 models is consideration of intermediate processes and products, in order to calculate the organization's overall efficiency. However, in conventional DEA, sub-stages of the organizations are neglected. To measure the efficiencies of an organization regarding interactive internal process, two case studies were investigated by application of the NDEA-MOP method with negative data. Case study 1 is focused on units with two stages having semi-negative and semi-positive indexes. In case study 2, units with three stages are evaluated. These units also have semi-negative and semi-positive indexes. The overall efficiency of each unit is calculated using the proposed models. Fuzzy approach as a solution procedure is applied.

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Section: Introductionmentioning

confidence: 99%

The NDEA–MOP Model in the Presence of Negative Data Using Fuzzy Method

et al. 2017

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show abstract

“…To illustrate the term of production example of input-output parameters in of production of blister copper (Cu b Outokumpu process, considered in [1] Figure 1. In this particular case we have parameter x (raw material -concentrate that cannot be modified, two intermed parameters between two stages (Cu 2 S, h.edu.pl ion strategies for production cha procha 2,a …”

Section: Introductionmentioning

confidence: 99%

“…While it is not has attached a sequence of ble values of input vector x i control parameters p i . re than 2 stages then the ranching points, creating a of production stages, as en strategies that can take al information about the n will be presented in the age linear chain of industrial n [1,2]). It is also worth noting, that to calculate v deeper levels of the tree, it is necess arrangement of stages.…”

Section: Introductionmentioning

confidence: 99%