A multicriteria sorting approach based on data envelopment analysis for R&D project selection problem

Omega ◽  
2017 ◽  
Vol 73 ◽  
pp. 79-92 ◽  
Author(s):  
Esra Karasakal ◽  
Pınar Aker
Keyword(s):  
Data Envelopment Analysis ◽  
Project Selection ◽  
Selection Problem ◽  
Data Envelopment ◽  
Multicriteria Sorting

Six sigma project selection using data envelopment analysis

2007 ◽  
Vol 19 (5) ◽  
pp. 419-441 ◽  
Author(s):  
U. Dinesh Kumar ◽  
Haritha Saranga ◽  
José E. Ramírez‐Márquez ◽  
David Nowicki
Keyword(s):  
Data Envelopment Analysis ◽  
Six Sigma ◽  
Project Selection ◽  
Data Envelopment ◽  
Using Data

A data envelopment analysis approach by partial impacts between inputs and desirable-undesirable outputs for sustainable supplier selection problem

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohammad Nemati ◽  
Reza Farzipoor Saen ◽  
Reza Kazemi Matin
Keyword(s):  
Data Envelopment Analysis ◽  
Supplier Selection ◽  
Selection Problem ◽  
Data Envelopment ◽  
Undesirable Outputs ◽  
Content Type ◽  
Dea Model ◽  
Sustainable Supplier Selection ◽  
Overall Efficiency ◽  
Supplier Selection Problem

PurposeThe objective of this paper is to propose a new data envelopment analysis (DEA) model for assessing sustainability of suppliers with partial impacts between inputs, desirable outputs and undesirable outputs.Design/methodology/approachThis paper examines partial impacts of inputs on desirable and undesirable outputs and applies weak disposability assumption to propose a novel DEA model to determine the sustainability of suppliers.FindingsThis paper shows the type of resource sharing in DEA models and takes into account sustainable development and sustainability assessment concepts for sustainable supplier selection problem and develops a DEA model for selecting the most sustainable suppliers with partial sharing of resources. To select the most sustainable suppliers, this model helps managers to consider aggregate efficiency, overall efficiency and bundle efficiency. The paper introduces the supplier which is efficient at all levels as the most sustainable supplier.Originality/valueFor the first time, this paper suggests a new DEA model by partial impact between inputs and good outputs/bad outputs for selecting sustainable supplier and deals with the situations in which each supplier has several subunits. The new model calculates aggregate efficiency, overall efficiency and subunit efficiency of supplier. paper introduces the supplier which is efficient in all levels including aggregate efficiency, overall efficiency and subunit efficiency as the best supplier.

scholarly journals NONLINEAR GENETIC-BASED MODEL FOR SUPPLIER SELECTION: A COMPARATIVE STUDY

2016 ◽  
Vol 23 (1) ◽  
pp. 178-195 ◽  
Author(s):  
Alireza FALLAHPOUR ◽  
Atefeh AMINDOUST ◽  
Jurgita ANTUCHEVIČIENĖ ◽  
Morteza YAZDANI
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Data Envelopment Analysis ◽  
Supplier Selection ◽  
Efficiency Score ◽  
Selection Problem ◽  
Data Envelopment ◽  
Data Set ◽  
Artificial Neural ◽  
Supplier Selection Problem

Evaluation and selection of candidate suppliers has become a major decision in business activities around the world. In this paper, a new hybrid approach based on integration of Gene Expression Programming (GEP) with Data Envelopment Analysis (DEA) (DEA-GEP) is presented to overcome the supplier selection problem. First, suppliers’ efficiencies are obtained through applying DEA. Then, the suppliers’ related data are utilized to train GEP to find the best trained DEA-GEP algorithm for predicting efficiency score of Decision Making Units (DMUs). The aforementioned data is also used to train Artificial Neural Network (ANN) to predict efficiency scores of DMUs. The proposed hybrid DEA-GEP is compared to integrated approach of Artificial Neural Network with Data Envelopment Analysis (DEA-ANN) to support the validity of the proposed model. The obtained results clearly show that the model based on GEP not only is more accurate than the DEA-ANN model, but also presents a mathematical function for efficiency score based on input and output data set. Finally, a real-life supplier selection problem is presented to show the applicability of the proposed hybrid DEA-GEP model.

scholarly journals Data Envelopment Analysis Approach to Energy-Saving Projects Selection in an Energy Service Company

Mathematics ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 200
Author(s):  
Gabriel Villa ◽  
Sebastián Lozano ◽  
Sandra Redondo
Keyword(s):  
Data Envelopment Analysis ◽  
Project Selection ◽  
Data Envelopment ◽  
Service Company ◽  
Service Companies ◽  
Energy Service ◽  
Energy Service Company ◽  
The Cost ◽  
Analysis Models ◽  
Selection Of

Project selection is a common problem for many companies. Specifically, it consists in identifying which projects should be selected with regard to their economic efficiency, i.e., the projects that maximise the profit they bring in while minimising the cost of the resources consumed. In this paper, we have focused our interest on energy service companies because of the importance of a convenient selection of their projects. In these types of companies, the attractiveness of a project depends on both the profit estimations obtained in simulations of the energy systems to be improved, as well as the probability that the project will be awarded (e.g., in local government bids, where typically several energy service companies compete to win the bid). We propose a new project selection method, especially tailored to energy service companies and based on centralised data envelopment analysis models with limited availability of the resources. This contrasts with all existing project selection methods and allows the proposed approach to make more efficient use of the limited resources. We have applied the model to a real-world case by selecting projects in a Spanish energy service company, showing the benefits of applying this approach, and comparing the results obtained with other data envelopment analysis project selection approaches.

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