TY - JOUR
T1 - Weighted-additive fuzzy multi-choice goal programming (WA-FMCGP) for supporting renewable energy site selection decisions
AU - Hocine, Amin
AU - Zhuang, Zheng Yun
AU - Kouaissah, Noureddine
AU - Li, Der Chiang
N1 - Funding Information:
The authors sincerely thank the following funding institutions for their grants in support of this research: Ministry of Science and Technology, Taiwan (Project no.: MOST108-2410-H-992-046 ), Czech Science Foundation (GACR), Czech Republic (Project no.: 18-13951S ), and UM Research Fund, Macau (Project no.: CPG2015-00017-FST).
Publisher Copyright:
© 2020 Elsevier B.V.
PY - 2020/9/1
Y1 - 2020/9/1
N2 - This paper proposes a novel weighted-additive fuzzy multi-choice goal programming (WA-FMCGP) model for the imprecise decision context wherein several conflicting goals are present but each goal has multiple-choice aspiration levels (MCALs) and, around them, the fuzzinesses are expressed in terms of membership functions (MFs). The main contribution of this model is its use of an objective function that minimises the weighted-additive summation of the normalised deviations; thus, the model can adopt any minimisation process from any goal programming (GP) variant. The advantages of this FGP-MCGP (fuzzy GP – multi-choice GP) model are shown by using it to solve a numerical example from F-MODM (fuzzy MODM) literature and comparing the results with those of a recent FP-MCGP (fuzzy programming – multi-choice GP) study. The application of the model is also verified using real data (i.e., it can model and support renewable energy site selection (RESS) where the decision context is imprecise). As WA-FMCGP is largely a MODM model, through its application, this study also provides a supplementary method in contrast to the multi-attribute decision-making (MADM) model applications used thus far for RESS.
AB - This paper proposes a novel weighted-additive fuzzy multi-choice goal programming (WA-FMCGP) model for the imprecise decision context wherein several conflicting goals are present but each goal has multiple-choice aspiration levels (MCALs) and, around them, the fuzzinesses are expressed in terms of membership functions (MFs). The main contribution of this model is its use of an objective function that minimises the weighted-additive summation of the normalised deviations; thus, the model can adopt any minimisation process from any goal programming (GP) variant. The advantages of this FGP-MCGP (fuzzy GP – multi-choice GP) model are shown by using it to solve a numerical example from F-MODM (fuzzy MODM) literature and comparing the results with those of a recent FP-MCGP (fuzzy programming – multi-choice GP) study. The application of the model is also verified using real data (i.e., it can model and support renewable energy site selection (RESS) where the decision context is imprecise). As WA-FMCGP is largely a MODM model, through its application, this study also provides a supplementary method in contrast to the multi-attribute decision-making (MADM) model applications used thus far for RESS.
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U2 - 10.1016/j.ejor.2020.02.009
DO - 10.1016/j.ejor.2020.02.009
M3 - Article
AN - SCOPUS:85080985344
SN - 0377-2217
VL - 285
SP - 642
EP - 654
JO - European Journal of Operational Research
JF - European Journal of Operational Research
IS - 2
ER -
