A preference-based multi-objective model for the optimization of best management practices

摘要: Summary The optimization of best management practices (BMPs) at the watershed scale is notably complex because social nature decision process, which incorporates information that reflects preferences makers. In this study, a preference-based multi-objective model was designed by modifying commonly-used Non-dominated Sorting Genetic Algorithm (NSGA-II). reference points, achievement scalarizing functions and an indicator-based principle were integrated for searching set preferred Pareto-optimality solutions. Pareto preference ordering also used reducing objective numbers in final decision-making process. This proposed then tested typical Three Gorges Region, China. results indicated more desirable solutions generated, reduced burden effort managers. Compare to traditional (GA), those concentrated narrow region close projection point instead entire Pareto-front. Based on ordering, with function values often (i.e., minimum cost solution pollutant load solution). authors’ view, new provides useful tool optimizing BMPs therefore great benefit