Recently, Assistant Professor He Xiaolei and Professor Zhang Weiguo from the Department of Management Science at our college published a high-quality academic paper titled "An Efficient Scenario Reduction Method for Problems with Higher Moment Coherent Risk Measures" in INFORMS Journal on Computing (IJOC). IJOC is one of the top journals recognized internationally in the UTD24 list and is published by the Institute for Operations Research and the Management Sciences (INFORMS). The paper lists Assistant Professor He Xiaolei as the first author, Professor Zhang Weiguo as the corresponding author, and Shenzhen University Management College as the sole affiliated institution.

According to statistics, since 2008, IJOC has published fewer than 25 papers solely authored by scholars and institutions from mainland China, two of which are co-authored by Professor Zhang Weiguo and Assistant Professor He Xiaolei.

The paper addresses stochastic programming models aimed at minimizing higher moment coherent risk measures (HMCR). It proposes a scenario reduction method based on the concept of ineffective scenarios. Existing methods primarily reduce the number of scenarios by minimizing a distance metric, often overlooking the structural characteristics of the optimization model, such as the fact that HMCR values depend only on a small subset of scenarios associated with high costs or losses, and not on others. The paper establishes some theoretical properties of HMCR measures, including dual representations and parameter ranges, and derives explicit expressions for ineffective scenarios when the optimal solution is known. Based on this, a new scenario reduction method is designed.

The paper applies this method to two portfolio problems of varying complexity. The results show that the method significantly reduces the number of scenarios while achieving more precise optimal values and solutions. The optimal portfolios also exhibit better diversification.

In recent years, our college has set the goal of building a first-class management discipline and a first-class management college. We have implemented incentive measures to encourage high-level research, both in theoretical studies at the forefront of academia and in applied research serving national strategies and the development of the Greater Bay Area, to promote high-quality output in discipline construction and talent cultivation.

College of Management

June 24, 2024