DATA ENVELOPMENT ANALYSIS WITH FUZZY RANDOM INPUTS AND OUTPUTS: A CHANCE-CONSTRAINED PROGRAMMING APPROACH
Authors
Abstract:
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 suitablemembership function, second, defuzzification of the parameters using an α-cut andfinally, converting the chance-constrained DEA into a crisp model using the methodof Cooper [4].
similar resources
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...
full textChance-constrained DEA models with random fuzzy inputs and outputs
Data Envelopment Analysis (DEA) is a widely used mathematical programming technique for comparing the inputs and outputs of a set of homogenous Decision Making Units (DMUs) by evaluating their relative efficiency. The conventional DEA methods assume deterministic and precise values for the input and output observations. However, the observed values of the input and output data in real-world pro...
full textA new approach based on alpha cuts for solving data envelopment analysis model with fuzzy stochastic inputs and outputs
Data Envelopment Analysis (DEA) is a widely used technique for measuring the relative efficiencies of homogenous Decision Making Units (DMUs) with multiple inputs and multiple outputs. These factors may be evaluated in fuzzy or stochastic environment. Hence, the classic structures of DEA model may be changed where in two fold fuzzy stochastic environment. For instances, linearity, feasibility a...
full textClassifying inputs and outputs in interval data envelopment analysis
Data envelopment analysis (DEA) is an approach to measure the relative efficiency of decision-making units with multiple inputs and multiple outputs using mathematical programming. In the traditional DEA, it is assumed that we know the input or output role of each performance measure. But in some situations, the type of performance measure is unknown. These performance measures are called flexi...
full textFuzzy random chance-constrained programming
By fuzzy random programming, we mean the optimization theory dealing with fuzzy random decision problems. This paper presents a new concept of chance of fuzzy random events and then constructs a general framework of fuzzy random chance-constrained programming (CCP). We also design a spectrum of fuzzy random simulations for computing uncertain functions arising in the area of fuzzy random progra...
full textSOME PROPERTIES FOR FUZZY CHANCE CONSTRAINED PROGRAMMING
Convexity theory and duality theory are important issues in math- ematical programming. Within the framework of credibility theory, this paper rst introduces the concept of convex fuzzy variables and some basic criteria. Furthermore, a convexity theorem for fuzzy chance constrained programming is proved by adding some convexity conditions on the objective and constraint functions. Finally,...
full textMy Resources
Journal title
volume 2 issue 2
pages 21- 29
publication date 2005-10-21
By following a journal you will be notified via email when a new issue of this journal is published.
Hosted on Doprax cloud platform doprax.com
copyright © 2015-2023