An integrated decision support framework for new energy vehicle evaluation based on regret theory and QUALIFLEX under Z-number environment

Abstract

New energy vehicles (NEVs) are the future of the automotive industry, with their development being highly significant for the energy system and environment. An important challenge faced by the automotive industry is appropriately assessing NEVs, which acts an important role in the promotion of NEV products and development of the NEV industry. This paper constructs an integrated decision support framework to solve NEV evaluation problems on the basis of information reliability, decision perception, and criterion non-compensation. By this means, the Z-number is introduced to reliably characterise the information involved in the problems, a Z-number regret theory model is established to identify the perceived utility of information, and QUALIFLEX outranking exploitation techniques are presented to comprehensively process multiple criterion assessments. To demonstrate the applicability of the constructed decision framework, a case study of NEV evaluation in Zhuzhou City is carried out and the result analysis and management implication are conducted in detail. The study reveals that the pure electric vehicle is evaluated as the most suitable NEV for development and production in Zhuzhou. Crucially, the analysis results confirm that the constructed framework can effectively facilitate NEV evaluation.