STOCHASTIC COST EFFICIENCY EVALUATION OF A SUPPLY CHAIN

M. MİRBOLOUKİ

Article Details

STOCHASTIC COST EFFICIENCY EVALUATION OF A SUPPLY CHAIN

Authors:

M. MİRBOLOUKİ

Publisher:

Turkic World Mathematical Society

Journal:

TWMS Journal of Applied and Engineering Mathematics 2016 Vol.6 Issue 1, pp.126-134

Document Type:

Article

Publication Date:

5/2016

Document Language:

English

Document ID (Org No.):

2000746215

Frequency:

Monthly

eISSN:

2587-1013

pISSN:

2146-1147

Abstract:

 

The main goal of the paper is a consideration of cost efficiency evaluation  models related to some supply chain when dealing with imprecise data. Data envelopment  analysis  DEA  method is a non-parametric mathematical programming approach to  assess the performance. This method is proposed for deterministic data and it can  be generalized to inaccurate data, while considering real world applications. Here we  consider data as random variables and after reviewing and introducing new models to  evaluate cost efficiencies related to the special circumstances of the supply chain using  DEA, these models are developed to probabilistic form. Also, deterministic and linear  equivalents are proposed using the symmetric error structure of normal distributions. At  final, by a numerical example, the proposed models are examined to show relationships  of results.

Article Details

STOCHASTIC COST EFFICIENCY EVALUATION OF A SUPPLY CHAIN

Authors: M. MİRBOLOUKİ

Publisher: Turkic World Mathematical Society

Journal: TWMS Journal of Applied and Engineering Mathematics 2016 Vol.6 Issue 1, pp.126-134

Document Type: Article

Publication Date: 5/2016

Document Language: English

Document ID (Org No.): 2000746215

Frequency: Monthly

eISSN: 2587-1013

pISSN: 2146-1147

Issues

Authors:

M. MİRBOLOUKİ

Publisher:

Turkic World Mathematical Society

Journal:

TWMS Journal of Applied and Engineering Mathematics 2016 Vol.6 Issue 1, pp.126-134

Document Type:

Article

Publication Date:

5/2016

Document Language:

English

Document ID (Org No.):

2000746215

Frequency:

Monthly

eISSN:

2587-1013

pISSN:

2146-1147