XOR analytic hierarchy process and its application in the renewable energy sector

Abstract Uncertainty is a ubiquitous and inherent feature of the decision-making process. This paper proposes a new method called the XOR-analytical hierarchy process (XOR-AHP) to solve multi-criteria decision-making problems in uncertain and imprecise environments. In particular, the method derives a priority vector from an XOR comparison matrix, an XOR weighting (XOR-W) technique based on mathematical programming that allows decision makers (DMs) to set multiple judgments for a particular evaluation using XOR logic. To incorporate DMs’ preferences in this process, three types of XOR matrices are proposed: optimistic, pessimistic, and neutral. How the new model offers an alternative way to support DMs under uncertain conditions and in imprecise environments is illustrated by considering a hypothetical application (ranking and selecting North African countries for RE investments in the case of the Desertec project).