基于双种群协同进化算法的城市水资源多目标优化配置——以宁波市海曙区为例OA

Aiming at the technical bottleneck of poor convergence and uneven distribution of solution sets when the traditional multi-objective optimization algorithm is used to deal with the strong constraint coupling problem of water resources allocation,this paper introduces the two-population co-evolutionary algorithm IMTCMO into the field of optimal allocation of water resources.The algorithm solves the problem of Pareto solution set degradation in high-dimensional objective space through the co-evolution mechanism of main and auxiliary tasks and dynamic constraint processing strategy.Taking Haishu District of Ningbo City as an example,an economic-social-ecological three-dimensional coupling optimal allocation model of water resources is constructed,in which the per capita water resources in Haishu District have approached the warning line of extreme water shortage.The IMTCMO algorithm is used to solve the water resources allocation schemes in 2030 and 2035 under different guarantee rates(50%,75%,90%),respectively,and compared with the classical NSGA-Ⅱ algorithm.The AHP-TOPSIS method is used to comprehensively evaluate the configuration scheme.The results show that:(a)the IMTCMO algorithm has a significant improvement in the economic benefit dimension compared with the NSGA-Ⅱ algorithm,and the comprehensive score of the optimal scheme is 0.629,which is 7.4%higher than the NSGA-Ⅱ algorithm;(b)the algorithm identifies the marginal benefit mutation point of reclaimed water in the range of 4.8%-14.1%of water supply ratio,and realizes the dynamic optimization of water supply structure;and(c)the configuration scheme presents the characteristics of"Peak clipping and valley filling",and under the guarantee rate of 90%,the total amount of water supply is actively controlled to avoid the sharp increase of marginal pollution cost.This research provides a scientific scheme for water resources management in Haishu District,verifies the application potential of the new generation of intelligent optimization algorithm in complex resource allocation problems,and provides a new way for the innovation of water resources allocation theory and method.