Few researches have inspected the task of green finance in reducing CO 2 emissions, while earlier studies have inspected the influence of economic development on carbon emissions. A green finance development index is built using four indicators to fill in this knowledge gap: green credit, green insurance, green securities, and green investing. Using data spanning the years 2005–2019, a panel quantile regression is applied to investigate the links between green finance, renewable energy, and CO 2 emissions. Increases in renewable energy use and advances in the green finance development index have contributed to a reduction in CO 2 emissions from BRICS countries. CO 2 emissions on the other hand slowed the growth of renewable energy use, slowed the flow of investment to green projects, and ultimately hampered the development of green finance. There was also a clear policy-driven influence on renewable energy spending in the countries of the BRICS region. Green finance policies, on the other hand, have consistently failed to have a long-term impact. Therefore, rising the consumption of renewable energy and creating a carbon trading market are all part of this study’s recommendations for green finance policy improvement.

This paper studies a special scheduling problem under hierarchical management in nurse staff. This is a more complex rostering problem than traditional nurse scheduling. The first is that the rostering requirements of charge nurses and general nurses are different under hierarchical management. The second is that nurses are preferable for relative fair rather than absolute fair under hierarchical management. The model aims at allocating the required workload to meet the operational requirements, weekend rostering preferences, and relative fairness preferences. Two hybrid heuristic algorithms based on multiobjective grey wolf optimizer (MOGWO) and three corresponding single heuristic algorithms are employed to solve this problem. The experimental results based on real cases from the Third People’s Hospital, Panzhihua, China, show that MOGWO does not as good as it does on other engineering optimization. However, the hybrid algorithms based on MOGWO are better than corresponding single algorithms on generational distance (GD) and spacing (SP) of Pareto solutions. Furthermore, for relative fair rostering objective, NSGAII-MOGWO has more power to find the optimal solution in the dimension of relative fairness.