| 英文摘要 |
Reducing greenhouse gas emissions is one major issue and challenge in transportation sections. To achieve this mission, various administrative divisions under the central government were asked to propose some low-carbon transport projects for annual budget planning and allocation. Instead of arbitrarily evaluating the performance of those projects, this paper contributes a method for quantifying and jointly optimizing the results of project selections and budget allocations, while also considering the proportion and minimum required amount of each proposed budget. A basic model (Model 1) adapted from the typical 0-1 knapsack problem, an extended mixed integer programming model (Model 2), and a multi-objective mixed integer nonlinear programming model (Model 3) are developed in this study. Models 1 and 2 are maximizing the total reduction of emissions based on selected projects and approved budget. Model 3 is further pursuing the equality issue by minimizing the variance of allocation results among administrative divisions. Through a series of numerical examples and sensitivity analysis, the models demonstrate their ability to maximize emissions reduction through budget allocating decisions. Different weight combinations between two objective functions are also examined. |