Linear Programming: Data Envelopment Analysis

2011 ◽  
pp. 175-210 ◽  
Keyword(s):  
Linear Programming ◽  
Data Envelopment Analysis ◽  
Data Envelopment

Strategic Choice and Data Envelopment Analysis: Comparing Computers across Many Attributes

1994 ◽  
Vol 9 (1) ◽  
pp. 61-69 ◽  
Author(s):  
John Doyle ◽  
Rodney Green
Keyword(s):  
Linear Programming ◽  
Regression Analysis ◽  
Data Envelopment Analysis ◽  
Multiple Regression Analysis ◽  
Multiple Regression ◽  
Strategic Choice ◽  
Programming Approach ◽  
Data Envelopment ◽  
Linear Programming Approach

A linear programming approach (Data Envelopment Analysis) is described to determine the relative merits of a set of multi-input, multi-output systems, in which more output for less input is considered good. The method is applied to benchmarks of microcomputers, and is contrasted with a multiple regression analysis of the same data. It is also argued that the essence of two opposing strategic outlooks can be captured within the method.

Decision to bid or not to bid: a data envelopment analysis approach

2010 ◽  
Vol 37 (1) ◽  
pp. 37-44 ◽  
Author(s):  
Mohammad S. El-Mashaleh
Keyword(s):  
Linear Programming ◽  
Data Envelopment Analysis ◽  
Analysis Approach ◽  
Programming Approach ◽  
Data Envelopment ◽  
Parametric Linear Programming ◽  
Linear Programming Approach ◽  
Selection Decisions ◽  
Dea Approach ◽  
Benchmarking Performance

One of the most crucial decisions that is regularly exercised by construction contractors is to determine whether to bid or not to bid on a certain project. The purpose of this paper is to propose a data envelopment analysis (DEA) approach for the bid–no-bid decision. DEA is a robust non-parametric linear programming approach that is used for benchmarking performance and for making selection decisions. Based on a contractor's database of previous considerations of bidding opportunities, DEA creates a “favorable frontier” that consists of favorable bidding opportunities. New bidding opportunities are evaluated in reference to this “favorable frontier” and the bid–no-bid decision is consequently made. The proposed approach incorporates subjective management expertise and deals systematically with bidding situations to guide contractors in their bid–no-bid determination. A major strength of the proposed DEA approach is that it is deployable by organizations facing the bid–no-bid problem regardless of size, country of operation, number and type of factors considered in bidding, or even industry.

The Measurement of Efficiency in Multiunit Public Services

1987 ◽  
Vol 19 (11) ◽  
pp. 1511-1524 ◽  
Author(s):  
W D Macmillan
Keyword(s):  
Linear Programming ◽  
Data Envelopment Analysis ◽  
Fractional Programming ◽  
Policy Formulation ◽  
Operating Conditions ◽  
Data Envelopment ◽  
Linear Fractional Programming ◽  
New Concepts ◽  
Nonlinear Version ◽  
Efficiency And Effectiveness

After a review of the concepts of efficiency and effectiveness in multiunit nonmarket organisations, a recently developed technique known as Data Envelopment Analysis (DEA) is described and illustrated in this paper, and it is shown how this technique may be used in performance measurement. The linear fractional programming and equivalent linear programming formulations of the DEA problem are presented and an illustrative problem is solved. Some new concepts concerned with the application of DEA are introduced. A nonlinear version of the DEA problem is then described and illustrated. A comparison is made between the solutions of the linear and the nonlinear DEA problems. Last, brief consideration is given to the problems of uncontrollable operating conditions, policy formulation, and the acceptability of the technique to unit managers.

scholarly journals Finding the Most Preferred Decision-Making Unit in Data Envelopment Analysis

2016 ◽  
Vol 2016 ◽  
pp. 1-8
Author(s):  
Shirin Mohammadi ◽  
S. Morteza Mirdehghan ◽  
Gholamreza Jahanshahloo
Keyword(s):  
Decision Making ◽  
Linear Programming ◽  
Data Envelopment Analysis ◽  
Utility Function ◽  
Decision Maker ◽  
Programming Models ◽  
Data Envelopment ◽  
Production Possibility ◽  
Decision Making Unit ◽  
Inputs And Outputs

Data envelopment analysis (DEA) evaluates the efficiency of the transformation of a decision-making unit’s (DMU’s) inputs into its outputs. Finding the benchmarks of a DMU is one of the important purposes of DEA. The benchmarks of a DMU in DEA are obtained by solving some linear programming models. Currently, the obtained benchmarks are just found by using the information of the data of inputs and outputs without considering the decision-maker’s preferences. If the preferences of the decision-maker are available, it is very important to obtain the most preferred DMU as a benchmark of the under-assessment DMU. In this regard, we present an algorithm to find the most preferred DMU based on the utility function of decision-maker’s preferences by exploring some properties on that. The proposed method is constructed based on the projection of the gradient of the utility function on the production possibility set’s frontier.

Perfect Partners of Mathematical Modeling with Technology in Risk Assessment

2016 ◽  
pp. 61-90
Author(s):  
William P. Fox
Keyword(s):  
Mathematical Modeling ◽  
Risk Assessment ◽  
Game Theory ◽  
Decision Making ◽  
Sensitivity Analysis ◽  
Linear Programming ◽  
Data Envelopment Analysis ◽  
Discrete Dynamical Systems ◽  
Data Envelopment ◽  
Multi Attribute Decision Making

This chapter discusses the use of mathematical modeling with technology in risk assessment in the broad area of operations research. The authors provide modeling as a process and illustrate suggested steps in the process. This chapter reviews some of the main modeling texts and provide a brief discussion of their processes. Many illustrative examples are provided to show the breadth of mathematical modeling. These examples cover such topics as discrete dynamical systems, game theory, multi-attribute decision making, data envelopment analysis with linear programming, and integer programming. The authors discuss the important of sensitivity analysis, as applicable. Several scenarios are used as illustrative examples of the process.

Assessing the Efficiency and Distribution of Agricultural Activities Using DSS

2011 ◽  
pp. 288-316
Author(s):  
Helga Pereira ◽  
Luis C. Dias ◽  
Maria João Alves
Keyword(s):  
Information System ◽  
Linear Programming ◽  
Data Envelopment Analysis ◽  
Geographical Information ◽  
Second Phase ◽  
Data Envelopment ◽  
Agricultural Activities ◽  
Mainland Portugal ◽  
Analysis Methodology

This work describes the sequential use of different Information Systems and Decision Support Systems (DSS) to measure the efficiency of a set of agricultural activities, and subsequently to propose alternative reallocations of these activities within a geographical region. The region selected as a case study was Ribatejo e Oeste (RO), an important agrarian region in mainland Portugal. The DEA (Data Envelopment Analysis) methodology was used to assess the efficiency of the most important agricultural activities in RO, using the Frontier Analyst DSS to study alternative modelling options. In a second phase, plans for redistributing the evaluated activities were studied, aiming at promoting the most efficient activities (according to DEA) but without creating at the same time drastic changes in current land uses. Several plans constituting different compromises between these two objectives were found using a multiobjective linear programming DSS. A Geographical Information System was used to constrain the areas that were adequate for each type of crop and to graphically illustrate some proposed plans.

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