Pairwise-comparison methods in multiple objective programming, with applications in a long-term energy-planning model

1985 ◽  
Vol 22 (1) ◽  
pp. 44-55 ◽  
Author(s):  
M. Kok ◽  
F.A. Lootsma
Keyword(s):  
Pairwise Comparison ◽  
Multiple Objective Programming ◽  
Energy Planning ◽  
Multiple Objective ◽  
Planning Model ◽  
Comparison Methods ◽  
Term Energy ◽  
Objective Programming

A spatial multi-period long-term energy planning model: A case study of the Greek power system

2014 ◽  
Vol 115 ◽  
pp. 456-482 ◽  
Author(s):  
Nikolaos E. Koltsaklis ◽  
Athanasios S. Dagoumas ◽  
Georgios M. Kopanos ◽  
Efstratios N. Pistikopoulos ◽  
Michael C. Georgiadis
Keyword(s):  
Power System ◽  
Energy Planning ◽  
Planning Model ◽  
Term Energy

FUZZY MULTIPLE OBJECTIVE PROGRAMMING IN AN INTERVAL PIECEWISE REGRESSION MODEL

2009 ◽  
Vol 17 (03) ◽  
pp. 365-376 ◽  
Author(s):  
JING-RUNG YU ◽  
GWO-HSHIUNG TZENG
Keyword(s):  
Regression Model ◽  
Regression Models ◽  
Heuristic Approach ◽  
Multiple Objective Programming ◽  
Change Points ◽  
Multiple Objective ◽  
Compromise Solution ◽  
Numerical Examples ◽  
Piecewise Regression ◽  
Objective Programming

This study proposes fuzzy multiple objective programming to determine the measure of fitness and the number of change-points in an interval piecewise regression model. To increase the measure of fitness, Tanaka and Lee proposed a conceptual procedure, which is a heuristic approach and becomes complicated for determining the proper polynomial. Therefore, a multiple objective approach is adopted to obtain a compromise solution among three objectives — maximizing the measure of fitness, minimizing the number of change-points and minimizing the width to obtain the interval regression models. By using the proposed method, a better measure of fitness can be obtained. Two numerical examples are used as demonstrations to illustrate our approach in more detail.

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