Optimizing sustainable and renewable energy portfolios using a fuzzy interval goal programming approach
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F20%3A10245949" target="_blank" >RIV/61989100:27510/20:10245949 - isvavai.cz</a>
Result on the web
<a href="https://reader.elsevier.com/reader/sd/pii/S0360835220301820?token=B2601CD7751F7C525D88F35D3C6EBB727E588555AF91EF84D3AF09923BA1335D3BEF7F35ECDD74359189FEFBFE4E38AC" target="_blank" >https://reader.elsevier.com/reader/sd/pii/S0360835220301820?token=B2601CD7751F7C525D88F35D3C6EBB727E588555AF91EF84D3AF09923BA1335D3BEF7F35ECDD74359189FEFBFE4E38AC</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.cie.2020.106448" target="_blank" >10.1016/j.cie.2020.106448</a>
Alternative languages
Result language
angličtina
Original language name
Optimizing sustainable and renewable energy portfolios using a fuzzy interval goal programming approach
Original language description
Determining the most sustainable renewable energy (RE) source portfolio that meets decision-maker preferences is a complicated and uncertain multi-criteria decision-making (MCDM) problem. The RE selection process involves meeting decision-makers' (DMs) preferences wherein several conflicting criteria are present, such as environmental, societal, and economic. Fuzzy goal programming (FGP) is one of the most well-known techniques for dealing with uncertainty existing in MCDM problems. However, conventional FGP techniques suppose only one single coefficient (or parameter) for each decision variable. This paper proposes a novel multi-objective decision-making model called fuzzy interval goal programming (FIGP) to release the restrictions of FGP with single-coefficient modeling. The proposed model can formulate an interval coefficient for each decision variable. To formulate such a model, this study adopts the concept of multi-choice aspiration levels (MCALs) from the revised multi-choice goal programming (RMCGP) technique. Specifically, the integrated model considers various types of fuzzy goals in real-world problems and offers DMs more flexibility to express and formulate their preferences in terms of fuzzy interval goals. The proposed method is illustrated by selecting the optimal RE portfolio for electricity generation in Italy. The relevant renewables are biomass, solar photovoltaic (PV), tidal currents, and wind energy. An empirical analysis shows that the proposed methodology is capable of assisting the DMs in ascertaining the optimal portfolio of RE under a high level of uncertainty and in imprecise environments.
Czech name
—
Czech description
—
Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
50200 - Economics and Business
Result continuities
Project
<a href="/en/project/GA18-13951S" target="_blank" >GA18-13951S: New approaches to financial time series modelling based on soft computing</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Computers and Industrial Engineering
ISSN
0360-8352
e-ISSN
—
Volume of the periodical
144
Issue of the periodical within the volume
June
Country of publishing house
GB - UNITED KINGDOM
Number of pages
12
Pages from-to
106448
UT code for WoS article
000535972200018
EID of the result in the Scopus database
2-s2.0-85084493403