Supplier selection using chance-constrained data envelopment analysis with non-discretionary factors and stochastic data

Supplier selection using chance- constrained data envelopment analysis with non-discretionary factors and stochastic data

The changing economic conditions have challenged many organizations to search for more efficient and effective ways to manage their supply chain. During recent years supplier selection decisions have received considerable attention in the supply chain management (SCM) literature. There are four major decisions that are related to the supplier selection process: what product or services to order...

Non-discretionary Factors in Data Envelopment Analysis: Review and Extension

Data Envelopment Analysis Models In The Presence Of Ratio Data and Non-Discretionary Factors

Supplier selection among alternative scenarios by Data envelopment analysis

A considerable problem in competitive trade world is choosing the best supply chain. As a result in much more serious circumstances of competitions looking for the best supplier for manufacturing, for preparing raw material, is very significant. Meantime suppliers have different scenarios to be fulfilled, such as changing selection variables like lead-time, transportation cost and transportatio...

DATA ENVELOPMENT ANALYSIS WITH FUZZY RANDOM INPUTS AND OUTPUTS: A CHANCE-CONSTRAINED PROGRAMMING APPROACH

In this paper, we deal with fuzzy random variables for inputs andoutputs in Data Envelopment Analysis (DEA). These variables are considered as fuzzyrandom flat LR numbers with known distribution. The problem is to find a method forconverting the imprecise chance-constrained DEA model into a crisp one. This can bedone by first, defuzzification of imprecise probability by constructing a suitablem...