scholarly journals Improving Energy Efficiency in Buildings Using an Interactive Mathematical Programming Approach

2021 ◽  
Vol 13 (8) ◽  
pp. 4436
Author(s):  
Christina Diakaki ◽  
Evangelos Grigoroudis

Improving energy efficiency in buildings is a major priority and challenge worldwide. The employed measures vary in nature, and the decision analyst, who is typically the architect, the engineer, or the building expert that has undertaken the task to suggest energy efficient solutions, faces a complex decision problem comprising numerous decision variables and multiple, usually competitive objectives. The solution of such multi-objective problems typically involves some sort of objectives aggregation, which reflects the preferences of the involved final decision maker that is the building’s user, occupant, and/or owner. The preferences elicitation, however, is a difficult task, and this paper aims to provide an interactive framework that will allow their consideration in a relatively easy manner. More specifically, a mathematical programming approach is proposed herein, which allows the elicitation and incorporation of the decision maker’s preferences in the decision model via the assessment of his/her utility function with the assistance of the multicriteria decision aid method UTASTAR. To study the feasibility and efficiency of the proposed approach, the case of a simple building is examined as an application example. The study results suggest that the proposed approach is capable of helping the decision analyst to suggest energy measures that satisfy, as much as possible, the decision maker’s preferences, without having to precisely prescribe them beforehand.

2008 ◽  
Vol 75 (1) ◽  
pp. 69-89 ◽  
Author(s):  
Hiroto Saigo ◽  
Sebastian Nowozin ◽  
Tadashi Kadowaki ◽  
Taku Kudo ◽  
Koji Tsuda

2021 ◽  
Author(s):  
Sheng-Hsing Nien ◽  
Liang-Hsuan Chen

Abstract This study develops a mathematical programming approach to establish intuitionistic fuzzy regression models (IFRMs) by considering the randomness and fuzziness of intuitionistic fuzzy observations. In contrast to existing approaches, the IFRMs are established in terms of five ordinary regression models representing the components of the estimated triangular intuitionistic fuzzy response variable. The optimal parameters of the five ordinary regression models are determined by solving the proposed mathematical programming problem, which is linearized to make the resolution process efficient. Based on the concepts of randomness and fuzziness in the formulation processes, the proposed approach can improve on existing approaches’ weaknesses with establishing IFRMs, such as the limitation of symmetrical triangular membership (or non-membership) functions, the determination of parameter signs in the model, and the wide spread of the estimated responses. In addition, some numerical explanatory variables included in the intuitionistic fuzzy observations are also allowed in the proposed approach, even though it was developed for intuitionistic fuzzy observations. In contrast to existing approaches, the proposed approach is general and flexible in applications. Comparisons show that the proposed approach outperforms existing approaches in terms of similarity and distance measures.


2014 ◽  
Vol 63 ◽  
pp. 674-680 ◽  
Author(s):  
S.D.O. Turner ◽  
D.A. Romero ◽  
P.Y. Zhang ◽  
C.H. Amon ◽  
T.C.Y. Chan

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