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Reference Point Based Multi-Objective Optimization of Reservoir Operation: a Comparison of Three Algorithms

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Indexed by:Journal Papers

Date of Publication:2020-02-01

Journal:WATER RESOURCES MANAGEMENT

Included Journals:EI、SCIE

Volume:34

Issue:3

Page Number:1005-1020

ISSN No.:0920-4741

Key Words:Multi-objective optimization; NSGA-II; Preference; Reservoir operation

Abstract:Traditional multi-objective evolutionary algorithms treat each objective equally and search randomly in all solution spaces without using preference information. This might reduce the search efficiency and quality of solutions preferred by decision makers, especially when solving problems with complicated properties or many objectives. Three reference point based algorithms which adopt preference information in optimization progress, e.g., R-NSGA-II, r-NSGA-II and g-NSGA-II, have been shown to be effective in finding more preferred solutions in theoretical test problems. However, more efforts are needed to test their effectiveness in real-world problems. This study conducts a comparison of the above three algorithms with a standard algorithm NSGA-II on a reservoir operation problem to demonstrate their performance in improving the search efficiency and quality of preferred solutions. Under the same calculation times of the objective functions, Pareto optimal solutions of the four algorithms are used in the empirical comparison in terms of the approximation to the preferred solutions. Three performance indicators are then adopted for further comparison. Results show that R-NSGA-II and r-NSGA-II can improve the search efficiency and quality of preferred solutions. The convergence and diversity of their solutions in the concerned region are better than NSGA-II, and the closeness degree to the reference point can be increased by 42.8%, and moreover the number of preferred solutions can be increased by more than 3 times when part of objectives are preferred. By contrast, g-NSGA-II shows worse performance. This study exhibits the performance of three reference point based algorithms and provides insights in algorithm selection for multi-objective reservoir optimization problems.

Pre One:Inherent Relationship between Flow Duration Curves at Different Time Scales: A Perspective on Monthl

Next One:Flash Flood Forecasting Based on Long Short-Term Memory Networks

Profile

丁伟，副教授，博导，长期从事流域水资源管理研究，主持国家自然科学基金项目青年基金1项、面上项目1项，十三五国家重点研发计划子课题1项、十四五国家重点研发计划子课题1项，作为技术骨干参与了国家自然科学基金重点项目、国际合作重点项目等多项课题。

发表SCI/EI论文30余篇，其中水文水资源领域顶级期刊《Water Resources Research》4篇（均为1作/通讯）、ASCE百年旗舰期刊《Journal of Water Resources Planning and Management》 4篇（3篇为1作/通讯）；授权国家发明专利4项、国际发明专利1项，且有1项实现百万成果转化；出版专著2部；获2019年辽宁省科技进步一等奖、2016年教育部科技进步一等奖、2021年大坝工程学会科技进步奖一等奖1项。

代表性论文

[1] Wei Ding, Bing Yu, Yong Peng^*, Guang Han, Lin Zhang, The marginal utility principles for a two-stage hydropower operation problem. Journal of Water Resources Planning and Management, 2022，DOI:10.1061/(ASCE)WR.1943-5452.0001556

[2] Xingsheng Shu, Wei Ding^*, Yong Peng^*, Ziru Wang, Jian Wu, Min Li. Monthly Streamflow Forecasting Using Convolutional Neural Network. Water Resources Management, 2021, 35(15): 5089-5104, DOI: 10.1007/s11269-021-02961-w

[3] Yu Li, Wei Ding^*, Xiaoxian Chen, Ximing Cai, Chi Zhang. An analytical framework for reservoir operation with combined natural inflow and controlled inflow, Water Resources Research,2020,56(8),e2019WR025347, Doi: 10.1029/2019WR025347

[4]Wei Ding, Haixing Liu^*, Yu Li, Hua Shang, Chi Zhang, Guangtao Fu. Unraveling the effects of long-distance water transfer for ecological recharge, Journal of Water Resources Planning and Management,2020,146(9):02520004, DOI: 10.1061/(ASCE)WR.1943-5452.0001272

[5] Bingyao Zhang, Wei Ding^*, Bo Xu, Longfan Wang, Yu Li, Chi Zhang. Spatial characteristics of total phosphorus loads from different sources in the Lancang River Basin, Science of The Total Environment,2020,722,137863, DOI: 10.1016/j.scitotenv.2020.137863

[6] Chi Zhang, Wei Ding^*, Yu Li, Fanlin Meng, Guangtao Fu. Cost-Benefit framework for optimal design of water transfer systems, Journal of Water Resources Planning and Management,2019,145(5):04019007, DOI:10.1061/(ASCE)WR.1943-5452.0001059

[7] Qiang Wang, Wei Ding^*, Yan Wang. Optimization of multi-reservoir operating rules for a water supply system, Water Resources Management,2018,32(14):4543-4559, DOI: 10.1007/s11269-018-2063-9

[8] Wei Ding, Chi Zhang ^*, Ximing Cai, Yu Li, Huicheng Zhou, Multiobjective hedging rules for flood water conservation, Water Resources Research, 2017,53(3):1963-1981, DOI: 10.1002/2016WR019452

[9] Chi Zhang, Wei Ding^*, Yu Li, Yin Tang, Dingbao Wang. Catchments' hedging strategy on evapotranspiration for climatic variability, Water Resources Research,2016,52(11):9036-9045, DOI：10.1002/2016WR019384

[10] Wei Ding, Chi Zhang^*, Yong Peng, Ruijie Zeng, Huicheng Zhou, Ximing Cai. An analytical framework for flood water conservation considering forecast uncertainty and acceptable risk, Water Resources Research,2015,51(6):4702-4726, DOI: 10.1002/2015WR017127

科研项目

[1] 国家重点研发计划课题，特大干旱条件下旱限（警）水位确定与抗旱应急智慧调度研究子课题：特大干旱下水利工程群应急调度技术研究，项目负责人

[2] 国家自然科学基金面上项目，基于知识学习的水库防洪智能调度研究，项目负责人

[3] 国家自然科学基金青年基金，水电站汛期防洪与发电协调控制理论与方法研究，项目负责人

[4] 国家重点研发计划，长江上游梯级水库群多目标联合调度技术子课题：面向两湖和长江口地区供水需求的水库群供水调度方案研究，项目负责人

[5] 水利前期项目，全国江河湖库旱限水位（流量）确定试点，技术负责人

[6] 吉林省农村基层项目，智慧水库洪水调度系统开发，技术负责人

[7] 国家自然基金重大国际合作研究项目，河库连通下的特大水库群联合调度基础问题研究，技术骨干

授权专利

[1] 魏国振，丁伟，梁国华，何斌，唐榕，王猛，马杏，周惠成，一种考虑预报误差降低水库洪水起调水位的预报调度方法,国内发明专利

[2] 丁伟，李昱，张弛，周惠成，一种基于成本-效益分析的跨流域引水工程规模确定方法，国内发明专利（实现百万成果转化）

出版专著

[1] 梁团豪，王晓妮，李昱，丁伟，松花江流域骨干水库联合调度，大连理工大学出版社，2019年

[2] 李清清，马超，吴江，丁伟，何小聪，适应多维度用水需求的水库群供水调度技术，中国水利水电出版社，2021年