Bilevel Optimization of Taxing Strategies for Carbon Emissions Using Fuzzy Random Matrix Generators

2. Literature Review

An example of BL optimization in sustainable development could be observed in the work Hu et al., (2019). In that work, the problem of conflicting resources of coal and water was considered. The authors analyzed this conflict from two angles: pollution issues and groundwater depletion. The problem formulation was then represented as a BL dynamic program in an uncertain environment that accounts for the relationship between the government and colliery enterprises. The primary aim of that work was to develop a reasonable mining quota allocation scheme based on economic development and environment protection - where a probability measure was employed to solve the problem of uncertainty. The model was then applied to a real-world case study and analyzed in the light of different scenarios (using sensitivity analysis). The problem was tackled using an interactive algorithm and the results show that the proposed methodology could help the government devise more strategic and sustainable mining quota schemes. A similar work in BL optimization is seen in Lin et al., (2018), where an incentive and coordination problem of a construction supply was considered (under an uncertain environment). The supply chain consisted of owner, general contractor, subcontractors and suppliers. The authors developed a BL nonlinear model where the owner initially decides on the proper intensities with the aim to minimize the total cost. Consequently, the general contractor determines the alternative and limit to subcontractors accordingly. The solution method employed in that work was the combination of interactive fuzzy approach and the genetic algorithm technique (GA). The proposed approach was then validated using a numerical example which optimizes the construction project management while respecting sustainable development constraints.