李永平
环境系统分析、水资源管理、城市环境规划、环境污染控制、 环境风险分析
个性化签名
- 姓名:李永平
- 目前身份:
- 担任导师情况:
- 学位:
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学术头衔:
博士生导师
- 职称:-
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学科领域:
环境科学技术
- 研究兴趣:环境系统分析、水资源管理、城市环境规划、环境污染控制、 环境风险分析
李永平
北京大学城市与环境学院资源与环境地理系研究员
研究方向:环境系统分析、水资源管理、城市环境规划、环境污染控制、 环境风险分析
(1) 教育背景(EDUCATION)
加拿大达尔豪西大学 (Dalhousie University) 资源与环境科学,博士后
加拿大里贾纳大学 (University of Regina) 环境系统工程,博士
加拿大里贾纳大学 (University of Regina) 环境系统工程,硕士
华中科技大学,工商管理硕士
武汉科技大学,工学学士
(2) 工作经历(WORK EXPERIENCES)
03/08 - 现在,北京大学城市与环境学院,研究员
02/07 - 03/08, 加拿大达尔豪西大学资源与环境科学,博士后研究员
07/91-11/02,武汉安全环保研究院,助理工程师、工程师
(3)奖励(AWARDS)
获加拿大里贾纳大学最高研究生奖(每年仅一位获奖人)(2007年10月)
获中国国家教育部优秀自费留学生奖(加拿大排名第一)(2007年3月)
(4)参加学术团体(PROFESSIONAL AFFILIATIONS)
International Society for Environmental Information Sciences (ISEIS)
International Association of Hydrological Sciences (IAHS)
(5)主持研究项目(RESEARCH PROJECTS):
1. 不确定性城市能源大气环境系统优化分析,中国国家科技部973项目(2005CB724200)子课题,负责人,2005-2010年
2. 不确定性跨流域湿地网络系统优化分析,中国国家科技部973项目(2006CB403300)子课题,负责人, 2006-2011年
3. 多重不确定性优化方法的研究及其在流域综合管理中的应用,国家基金委主任基金项目,负责人(50849002),2008-2009年
4. 城市重大突发环境污染事件应急技术机制, 环境模拟与污染控制国家重点联合实验室开放课题(08ESPCT-K),负责人,2009-2010年
5. 不确定性条件下流域水资源开发与管理方法的研究, 水沙科学与水利水电工程国家重点实验室开放课题(sklhse-2008-A-01), 负责人,2009-2010年
6.基于水环境与水资源承载能力的滨海新区工业园区布局优化研究/滨海新区工业园区产业布局优化方案与技术途径研究,国家水体污染控制与治理科技重大专项子课题,主要参加,2008-2010年
7. 不确定性优化方法用于流域水资源管理的研究, 留学回国人员科研启动基金, 负责人,2009-2010年
8. 基于遥感的塔里木河流域水资源管理模型,负责人,2010-2011年
9.干旱区区域水循环蒸散发模型参数优化研究,负责人,2010-2011年
10.水资源系统的模糊-随机规划与多判据决策分析,国家自然科学基金面上项目(50979001),负责人,2010-2012年
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主页访问
1673
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关注数
0
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成果阅读
707
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成果数
14
李永平, Y.P. Li a, ∗, G.H. Huangb, , N. Zhangc, S.L. Nied
Ecological Modelling xxx(2009)xxx-xxx,-0001,():
-1年11月30日
Effective planning of resources management is important for facilitating socio-economic development and eco-environmental sustainability. Such a planning effort is complicated with a variety of uncertain, dynamic and nonlinear factors as well as their interactions. In this study, an inexact-stochastic quadratic programming with recourse (ISQP-R) method is developed for reflecting dynamics of system uncertainties based on a complete set of scenarios as well as tackling nonlinearities in the objective function to reflect the effects of marginal utility on system benefits and costs. Moreover, since penalties are exercised with recourse against any infeasibility, the ISQP-R can support the analysis of various policy scenarios that are associated with different levels of economic consequences when the promised targets are violated. The developed method is applied to a case study of planning resources management and developing regional ecological sustainability. The results have been generated and are helpful for decision makers in not only identifying desired resources-allocation strategies but also gaining insight into the tradeoff between economic objective and eco-environment violation risk.
Decision making, Ecological, Modeling, Optimization, Stochastic with recourse, Sustainability, Uncertainty, Resources management
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引用
李永平, Y.P. Li a, *, G.H. Huang b, c, , P. Guo c, Z.F. Yang d, S.L. Nie e
European Journal of Operational Research 200(2010)536-550,-0001,():
-1年11月30日
In this study, a dual-interval vertex analysis (DIVA) method is developed, through incorporating the vertex method within an interval-parameter programming framework. The developed DIVA method can tackle uncertainties presented as dual intervals that exist in the objective function and the left- and right-hand sides of the modeling constraints. An interactive algorithm and a vertex analysis approach are proposed for solving the DIVA model. Solutions under an associated a-cut level can be generated by solving a series of deterministic submodels. They can help quantify relationships between the objective function value and the membership grade, which is meaningful for supporting in-depth analyses of tradeoffs between environmental and economic objectives as well as those between system optimality and reliability. A management problem in terms of regional air pollution control is studied to illustrate applicability of the proposed approach. The results indicate that useful solutions for planning the air quality management practices have been generated. They can help decision makers to identify desired pollution-abatement strategies with minimized costs and maximized environmental efficiencies.
Air quality, Decision making, Dual interval, Environment, Fuzzy programming, Optimization, Vertex analysis, Uncertainty
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80浏览
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李永平, Y.P. Li a, ∗, G.H. Huangb, , S.L. Niec
Resources, Conservation and Recycling 54(2009)86-96,-0001,():
-1年11月30日
In this study, a robust interval-based minimax-regret analysis (RIMA) method is developed and applied to the identification of optimal water-resources-allocation strategies under uncertainty. The developed RIMAapproachcan address uncertainties with multiple presentations.Moreover, it can be usedfor analyzing all possible scenarios associated with different system costs/benefits and risk levels without making assumptions on probabilistic distributions for random variables. In its solution process, an intervalelement cost/benefit matrix can be transformed into an interval-element regret matrix, such that the decision makers can identify desired strategies based on inexact minimax regret (IMMR) criterion. Moreover, the fuzzy decision space is delimited into a more robust one through dimensional enlargement of the original fuzzy constraints. The developed method is applied to a case study of planning water resources allocation under uncertainty. The results indicate that reasonable solutions have been generated. They can help decision makers identify desired strategies for water-resources allocation with a compromise between maximized system benefit and minimized system-failure risk.
Decision making, Fuzzy sets, Interval-based, Minimax regret, Planning, Robust programming, Uncertainty, Water resources
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56浏览
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李永平, Y.P. Li *, G.H. Huang
Information Sciences 179(2009)4261-4276,-0001,():
-1年11月30日
In this study, a fuzzy-stochastic-based violation analysis (FSVA) approach is developed for the planning of water resources management systems with uncertain information, based on a multistage fuzzy-stochastic integer programming (FSIP) model. In FSVA, a number of violation variables for the objective and constraints are allowed, such that in-depth analyses of tradeoffs among economic objective, satisfaction degree, and constraint-violation risk can be facilitated. Besides, the developed method can deal with uncertainties expressed as probability distributions and fuzzy sets; it can also reflect the dynamics in terms of decisions for water-allocation and surplus-flow diversion, through transactions at discrete points of a complete scenario set over a multistage context. The developed FSVA method is applied to a case study of water resources management within a multi-stream, multi-reservoir and multi-period context. The results indicate that the satisfaction degrees and system benefits would be different under varied violation levels; moreover, different violation levels can also lead to changed water-allocation and surplus-flow diversion plans. Violation analyses are also conducted to demonstrate that violating different constraints have different effects on system benefit and satisfaction degree.
Decision making, Fuzzy programming, Planning, Stochastic, Uncertain information, Violation analysis, Water resources
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65浏览
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李永平, Y.P. Li a, b, *, G.H. Huang b, c, , G.Q. Wanga, Y.F. Huang a
Agricultural Water Management 96(2009)1807-1818,-0001,():
-1年11月30日
A hybrid fuzzy-stochastic water-management (FSWM) model is developed for agricultural sustainability under uncertainty, based on advancement of a multistage fuzzy-stochastic quadratic programming (MFSQP) approach. In MFSQP, uncertainties presented in terms of fuzziness and randomness can be incorporated within a multilayer scenario tree, such that revised decisions are permitted in each time period based on the realized values of the uncertain events. Moreover, fuzzy quadratic terms are used in the objective function to minimize the variation of satisfaction degrees among the constraints; it allows an increased flexibility in controlling the system risk in the optimization process. Results of the case study indicate that useful solutions for the planning of agricultural water management have been obtained. In the FSWM model, a number of policies for agricultural water supply are conducted. The results obtained can help decision makers to identify desired water-allocation schemes for agricultural sustainability under uncertainty, particularly when limited water resources are available for multiple competing users.
Fuzzy quadratic programming, Multistage, Optimization, Policy analysis, Stochastic, Uncertainty, Water management
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【期刊论文】Two-stage planning for sustainable water-quality management under uncertainty
李永平, Y.P. Li a, *, G.H. Huang b, c,
Journal of Environmental Management 90(2009)2402-2413,-0001,():
-1年11月30日
In water-quality management problems, uncertainties may exist in a number of impact factors and pollution-related processes (e.g., the volume and strength of industrial wastewater and their ariations can be presented as random events through identifying a statistical distribution for each source); moreover, nonlinear relationships may exist among many system components (e.g., cost parameters may be functions of wastewater-discharge levels). In this study, an inexact two-stage stochastic quadratic programming (ITQP) method is developed for water-quality management under uncertainty. It is a hybrid of inexact quadratic programming (IQP) and two-stage stochastic programming (TSP) methods. The developed ITQP can handle not only uncertainties expressed as probability distributions and interval values but also nonlinearities in the objective function. It can be used for analyzing various scenarios that are associated with different levels of economic penalties or opportunity losses caused by improper policies. The ITQP is applied to a case of water-quality management to deal with uncertainties presented in terms of probabilities and intervals and to reflect dynamic interactions between pollutant loading and water quality. Interactive and derivative algorithms are employed for solving the ITQP model. The solutions are presented as combinations of deterministic, interval and distributional information, and can thus facilitate communications for different forms of uncertainties. They are helpful for managers in not only making decisions regarding wastewater discharge but also gaining insight into the tradeoff between the system benefit and the environmental requirement.
Environment, Optimization, Planning, Quadratic programming, Two-stage, Uncertainty, Water quality
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【期刊论文】Inexact fuzzy-stochastic constraint-softened programming-A case study for waste management
李永平, Y.P. Li a, *, G.H. Huang b, c, Z.F. Yang d, X. Chen e
Waste Management 29(2009)2165-2177,-0001,():
-1年11月30日
In this study, an inexact fuzzy-stochastic constraint-softened programming method is developed for municipal solid waste (MSW) management under uncertainty. The developed method can deal with multiple uncertainties presented in terms of fuzzy sets, interval values and random variables. Moreover, a number of violation levels for the system constraints are allowed. This is realized through introduction of violation variables to soften system constraints, such that the model's decision space can be expanded under demanding conditions. This can help generate a range of ecision alternatives under various conditions, allowing in-depth analyses of tradeoffs among economic objective, satisfaction degree, and constraint-violation risk. The developed method is applied to a case study of planning a MSW management system. The uncertain and dynamic information can be incorporated within a multi-layer scenario tree; revised decisions are permitted in each time period based on the realized values of uncertain events. Solutions associated with different satisfaction degree levels have been generated, corresponding to different constraint-violation risks. They are useful for supporting decisions of waste flow allocation and system-capacity expansion within a multistage context.
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李永平, Y.P. Li a, *, G.H. Huang b, c, , Y.F. Huang d, H.D. Zhou e
Environmental Modelling & Software 24(2009)786-797,-0001,():
-1年11月30日
In this study, a multistage fuzzy-stochastic programming (MFSP) model is developed for tackling uncertainties presented as fuzzy sets and probability distributions. A vertex analysis approach is proposed for solving multiple fuzzy sets in the MFSP model. Solutions under a set of a-cut levels can be generated by solving a series of deterministic submodels. The developed method is applied to the planning of a case study for water-resources management. Dynamics and uncertainties of water availability (and thus water allocation and shortage) could be taken into account through generation of a set of representative scenarios within a multistage context. Moreover, penalties are exercised with recourse against any infeasibility, which permits in-depth analyses of various policy scenarios that are associated with different levels of economic consequences when the promised water-allocation targets are violated. The modeling results can help to generate a range of alternatives under various system conditions, and thus help decision makers to identify desired water-resources management policies under uncertainty.
Decision making, Dynamics, Fuzzy sets, Multistage, Stochastic analysis, Uncertainty, Water resources
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李永平, Yongping Li, * and Gordon H. Huang,
ENVIRONMENTAL ENGINEERING SCIENCE Volume 26, Number 1, 2009,-0001,():
-1年11月30日
In real-world municipal solid waste (MSW) management systems, identification of proper policies under uncertainty for accomplishing desired waste-disposal targets is critical. An inexact minimax regret integer programming (IMMRIP) method for the long-term planning of MSW management is developed. It incorporates the technique of minimax regret analysis (MMR) into an interval-parameter mixed-integer linear programming (IMILP) framework. The IMMRIP method can handle dual uncertainties presented as both random variables and interval values; it only needs a list of scenarios without any assumption on their probability distributions. It can facilitate dynamic analysis for decisions of system-capacity expansion and/or development within a multi-facility and multi-period context. Moreover, it can also be used for analyzing multiple scenarios associated with different system costs and risk levels. An interval-element cost matrix can be transformed into an interval-element regret matrix based on an interactive algorithm. Solutions based on an inexact minimax regret criterion can identify desired alternatives for MSW management and planning under a variety of uncertainties. In a companion paper, the developed method will be applied to a real case study in the City of Regina, Canada.
decision making, environment, inexact optimization, minimax regret, mixed integer linear programming, solid waste, uncertainty
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李永平, Yongping Li and Gordon H. Huang, , *
ENVIRONMENTAL ENGINEERING SCIENCE Volume 26, Number 1, 2009,-0001,():
-1年11月30日
In this study, an inexact minimax regret mixed integer programming (IMMRIP) method is applied to long-term planning of municipal solid waste (MSW) management in the City of Regina. The method can help tackle the dynamic, interactive, and uncertain characteristics of the solid waste management system in the city, and can address issues concerning plans for cost-effective waste diversion and landfill prolongation. Thirty-six situations were examined based on multiple alternatives and scenarios under different waste-generation levels. Reasonable solutions have been generated for decisions of system-capacity expansion and waste-flow allocation, demonstrating complex tradeoffs among system cost, regret level, and constraint-violation risk. Solutions associated with further inexact minimax regret (IMMR) analyses can help tackle tradeoffs between minimized system cost and maximized system feasibility. Under the optimal alternative, the system would reach a maximum reliability with the lowest risks of penalty and wastage. Results provide valuable inputs for adjustment of the existing waste flow allocation patterns to satisfy the city's diversion goals, long-term capacity planning for the city's waste management system, and generation desired policies for managing the city's waste collection and treatment.
decision making, diversion, environment, planning, scenario analysis, solid waste, uncertainty
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