Assessment of Medical Service Pricing in China's Healthcare System: Challenges, Constraints, and Policy Recommendations

Medical service pricing reform was considered as one of the focuses of China's remarkable health reform. This paper preliminarily assessed the roles of medical service pricing in the context of China's healthcare system. Specifically, we described the potential roles of medical service pricing in China and pointed out relevant challenges that emerged in practice as the result of reform-related activities. Multiple constraint factors that might have induced undesired outcomes were then recognized, including the excessive diversity and specialization of medical services, the price inelasticity of patients' demand, and the inadequate capability of both medical institutions and administrations. Finally, we provided policy recommendations to inform the ongoing medical service pricing reform in China from a long-term perspective.

ACO with Intuitionistic Fuzzy Pheromone Updating Applied on Multiple-Constraint Knapsack Problem

Some of industrial and real life problems are difficult to be solved by traditional methods, because they need exponential number of calculations. As an example, we can mention decision-making problems. They can be defined as optimization problems. Ant Colony Optimization (ACO) is between the best methods, that solves combinatorial optimization problems. The method mimics behavior of the ants in the nature, when they look for a food. One of the algorithm parameters is called pheromone, and it is updated every iteration according quality of the achieved solutions. The intuitionistic fuzzy (propositional) logic was introduced as an extension of Zadeh’s fuzzy logic. In it, each proposition is estimated by two values: degree of validity and degree of non-validity. In this paper, we propose two variants of intuitionistic fuzzy pheromone updating. We apply our ideas on Multiple-Constraint Knapsack Problem (MKP) and compare achieved results with traditional ACO.

Accessibility analysis of distance education resources based on multiple constraint model

In recent years, more and more attention has been paid to the equity issues in education, Many Chinese families hope to change the fate of their children through educational equity. Based on the theory of accessibility, this paper analyzes the accessibility of distance education resources by using multi constraint model. The primary school education resources in the former Haishu District of Ningbo City are taken as examples to evaluate the accessibility to educational resources in all the primary schools in the district under the walking mode, the public transport mode, and the driving mode, respectively. The study shows that the areas with high accessibility to education resources in Haishu District are mainly distributed in places with developed road networks, large scale schools, and developed public transport networks, while those places with low accessibility are mainly located in the peripheral area. There are significant differences in the accessibility under different modes of transport, and the accessibility in the driving mode is superior to that in the public transport mode and the walking mode. In comparison, the correction effect on the accessibility in the public transport mode and the driving mode is average. Based on the multiple constraint model, the correction effect on the accessibility in the walking mode is significant. According to the analysis results, suggestions are put forward to promote the balanced development of educational resources in the Haishu District.

Handling of Constraints in Efficient Global Optimization

Although the Efficient Global Optimization (EGO) algorithm has been widely used in multi-disciplinary optimization, it is still difficult to handle multiple constraint problems. In this study, to increase the accuracy of approximation, the Least Squares Support Vector Regression (LSSVR) is suggested to replace the kriging model for approximating both objective and constrained functions while the variances of these surrogate models are still obtained by kriging. To enhance the ability to search the feasible region, two criteria are suggested. First, a Maximize Probability of Feasibility (MPF) strategy to handle the infeasible initial sample points is suggested to generate feasible points. Second, a Multi-Constraint Parallel (MCP) criterion is suggested for multiple constraints handling, parallel computation and validation, respectively. To illustrate the efficiency of the suggested EGO-based method, several deterministic benchmarks are tested and the suggested methods demonstrate a superior performance compared with two other constrained algorithms. Finally, the suggested algorithm is successfully utilized to optimize the fiber path of variable-stiffness beam and lightweight B-pillar to demonstrate the performance for engineering applications.