Based on the multi-level structure attributes of regional logistics, regional logistics integration presents complex features. Therefore, according to the operational requirements of regional logistics integration, we built a regional logistics network structure model consisting of infrastructure, information resources, and organizational networks; selected the level of relationship between different layers and information dissemination, and transport flow as decision variables. We built a supernetwork mathematical model of regional logistics integration with multiple layers of attributes. Considering the constraints of marginal cost changes and overall revenue, we found an equilibrium solution for the operation of regional logistics integration supernetwork. That is, the optimal match between the level of relationship, the level of information dissemination and the transportation flow, provides a reference basis for the formulation of relevant policies and implementation strategies.
Objective recognition of higher education development status and competitiveness is an important prerequisite and foundation for the transformation and development of regional higher education. At present, the identification and analysis methods for solving this problem cannot get rid of the subjective intention of reviewers or managers completely, and still adopt a unified evaluation standard. This makes the credibility of the results not high, resulting in not ideal implementation of follow-up policies and measures. In view of this, this paper proposes a method of individual advantage feature recognition to identify and evaluate regional higher competitiveness. This method is based on the description of the multi-indexes system of objects, and chooses the goal programming evaluation method to construct the mathematical model of individual superiority characteristic recognition, and explores the individual superiority characteristics of the regional higher education. This evaluation structure has intuitive interpretation and is easy to understand and accept.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.