scholarly journals A Parametric Testing Of The Firefly Algorithm In The Determination Of The Optimal Osmotic Drying Parameters Of Mushrooms

2014 ◽  
Vol 4 (4) ◽  
pp. 257-266 ◽  
Author(s):  
Julian Scott Yeomans
Keyword(s):  
Firefly Algorithm ◽  
Programming Model ◽  
Optimal Parameter ◽  
Osmotic Dehydration ◽  
Relative Sensitivity ◽  
Computationally Efficient ◽  
Linear Goal Programming ◽  
Goal Programming Model ◽  
Response Surface Technique ◽  
Parametric Testing

Abstract The Firefly Algorithm (FA) is employed to determine the optimal parameter settings in a case study of the osmotic dehydration process of mushrooms. In the case, the functional form of the dehydration model is established through a response surface technique and the resulting mathematical programming is formulated as a non-linear goal programming model. For optimization purposes, a computationally efficient, FA-driven method is used and the resulting optimal process parameters are shown to be superior to those from previous approaches. The final section of this study provides a computational experimentation performed on the FA to analyze its relative sensitivity over a range of the two key parameters that most influence its running time.

A Linear Goal Programming Model for Weight Calculation in Fuzzy AHP and its Application in Product Development

2010 ◽  
Vol 118-120 ◽  
pp. 712-716 ◽  
Author(s):  
Li Jun Yan ◽  
Zong Bin Li ◽  
Xiao Chun Yang
Keyword(s):  
Product Development ◽  
Goal Programming ◽  
Programming Model ◽  
Pairwise Comparison ◽  
Analysis Method ◽  
Pairwise Comparison Matrix ◽  
Wrong Decision ◽  
Comparison Matrix ◽  
Linear Goal Programming ◽  
Goal Programming Model

The key issue of FAHP application is how to derive fuzzy weights from fuzzy pairwise comparison matrix. The most of applications, however, were founding avoiding the use of sophisticated approaches such as fuzzy least squares method and using a simple extent analysis method to derive fuzzy weight from pairwise comparison matrix for the sake of simplicity. But the extent analysis method proves to be incorrect and may lead to a wrong decision result. So, this paper proposes a sound yet simple linear goal programming model to derive weights from pairwise fuzzy comparison matrix, which takes minimizing inconsistence degree of comparison matrix as objective and obtain a normalized weight vector finally. The proposed model is validated by an application to new product development scheme screening decision making.

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