In contrast, minimum cost of dredging projects is discovered when weight factor of cost is 1.0. Besides, the maximum cost is obtained when weight factor of social impact is 1.0.
According to model simulation, it shows that cost of dredging is different approximately 18% due to weight factors. The multi-objective optimization is used equality weight factors combination or weight factors from previous study. The single-objective optimization is same that one weight factor is 1.0 and other weight factor is 0.0. The first category is weight factors combination for single-objective optimization and another category is weight factors combination for multi-objective optimization. It can classify weight factors combination in 2 categories. We used a total of 5 cases of weight factors combination. Furthermore, for the model development, the researcher applied imaginary dredging project area for model assessment and analysis. This model requires various input data which are dredging points, dredging machines, dewatering machines, disposal sites. This model supports the decision making by providing weight factors covering dredging cost, and social and environmental impacts. The main purpose of this study is to develop an optimal river dredging management model by applying MCDA (Multi-Criteria Decision Analysis) technique specifically in Korea where river dredging research are scarce.
0 kommentar(er)
