ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, vol.127, 2024 (SCI-Expanded)
An emerging question for photovoltaic (PV) solar power development is how to ascertain the
optimal choice from a finite set of available alternatives under numerous conflicting criteria as
well as high levels of imprecise, vague, and uncertain information. For the first time, we investigate
the prioritization of the alternatives for the development of PV solar power via the interval-valued
intuitionistic fuzzy sets (IVIFSs), which show great power in capturing ambiguous, uncertain, and
vague information, and mitigating information loss. This paper presents a novel integrated
intelligent decision support system comprising of Strengths, Weaknesses, Opportunities, and
Threats (SWOT) analysis, Analytic Hierarchy Process (AHP), and Combined Compromise
Solution (CoCoSo) within an interval-valued intuitionistic fuzzy (IVIF) framework. Four
alternatives are considered. To rank these alternatives, twelve criteria are defined under four
aspects of SWOT analysis based on literature review and discussion with decision-makers.
Subsequently, the IVIF-AHP method is utilized to determine the weights assigned to each criterion
and sub-criterion. Finally, the IVIF-CoCoSo method is employed to rank four alternatives. The
results showed that giving proactive attention to mitigating potential adverse environmental
impacts of PV solar systems is the most highly prioritized strategy for PV solar power development.
The results of the comparative and sensitivity analyses showed that the proposed method generates
highly robust outcomes. The formulated integrated intelligent decision support system can help
energy policy authorities with a valuable resource to craft optimal techniques for developing PV
solar power.