Abstract
Multilevel programming is a mathematical programming problem with hierarchical structure. A typical feature of multilevel programming is that the upper level exhibits a priority over the lower level. However, the solutions obtained by most existing programming methods either violate this rule or ignore the participants' desire for a win-win outcome. The objective of this study is to propose new multilevel programming approaches for obtaining desirable solutions. First, three types of membership functions in neutrosophic set are defined to comprehensively describe fuzzy cognition of decision makers. Then, considering dissimilar intentions of experts, three different interactive approaches are proposed to solve multilevel programming problems. To demonstrate the feasibility of the proposed approaches, a case of pricing decision-making of data products is investigated and the impacts of four key parameters are discussed. Finally, several numerical examples are studied by using the proposed approaches and other existing methods. Two evaluation indexes, the equilibrium coefficient and distance measure, are utilized to appraise the performance of the developed programming methods. The results demonstrate that the proposed approaches can obtain sound solutions which obey the rule of multilevel programming, realize the mutual benefits of participants, and can provide guidelines for the pricing of satellite image data products.