Finding efficient assignments: An innovative DEA approach

Esmaiel Keshavarz, Mehdi Toloo*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)


Finding and classifying all efficient assignments for a Multi-Criteria Assignment Problem (MCAP) is one of the controversial issues in Multi-Criteria Decision Making (MCDM) problems. The main aim of this study is to utilize Data Envelopment Analysis (DEA) methodology to tackle this issue. Toward this end, we first state and prove some theorems to clarify the relationships between DEA and MCAP and then design a new two-phase approach to find and classify a set of efficient assignments. In Phase I, we formulate a new Mixed Integer Linear Programming (MILP) model, based on the Additive Free Disposal Hull (FDH) model, to gain an efficient assignment and then extend it to determine a Minimal Complete Set (MCS) of efficient assignments. In Phase II, we use the BCC model to classify all efficient solutions obtained from Phase I as supported and non-supported. A 4 × 4 assignment problem, containing two cost-type and single profit-type of objective functions, is solved using the presented approach.

Original languageEnglish
Pages (from-to)448-458
Number of pages11
JournalMeasurement: Journal of the International Measurement Confederation
Publication statusPublished - Dec 1 2014
Externally publishedYes


  • Additive FDH model
  • Data Envelopment Analysis (DEA)
  • Multi-Criteria Assignment Problem (MCAP)
  • Multi-Criteria Decision Making (MCDM)
  • Non-dominated point
  • Supported efficient assignment

ASJC Scopus subject areas

  • Instrumentation
  • Electrical and Electronic Engineering

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