Combining Data Envelopment Analysis and Machine Learning

Data envelopment analysis classification machine

Article history: Received 4 December 2009 Received in revised form 1 June 2011 Accepted 2 July 2011 Available online 12 July 2011

Combining data envelopment analysis and multi-objective model for the efficient facility location–allocation decision

This paper proposes an innovative procedure of finding efficient facility location–allocation (FLA) schemes, integrating data envelopment analysis (DEA) and a multi-objective programming (MOP) model methodology. FLA decisions provide a basic foundation for designing efficient supply chain network in many practical applications. The procedure proposed in this paper would be applied to the FLA pr...

An Intelligence-Based Model for Supplier Selection Integrating Data Envelopment Analysis and Support Vector Machine

The importance of supplier selection is nowadays highlighted more than ever as companies have realized that efficient supplier selection can significantly improve the performance of their supply chain. In this paper, an integrated model that applies Data Envelopment Analysis (DEA) and Support Vector Machine (SVM) is developed to select efficient suppliers based on their predicted efficiency sco...

Failure Mode and Effects Analysis Using Data Envelopment Analysis

Complex-Valued Data Envelopment Analysis

Data Envelopment Analysis (DEA) is a nonparametric approach for measuring the relative efficiency of a decision making units consists of multiple inputs and outputs. In all standard DEA models semi positive real valued measures are assumed, while in some real cases inputs and outputs may take complex valued. The question is related to measuring efficiency in such cases. As far as we are aware, ...