共查询到20条相似文献,搜索用时 562 毫秒
1.
Imran Maqsood Guo H. Huang 《Stochastic Environmental Research and Risk Assessment (SERRA)》2013,27(3):643-657
This study introduces a hybrid optimization approach for flood management under multiple uncertainties. An inexact two-stage integer programming (ITIP) model and its dual formation are developed by integrating the concepts of mixed-integer and interval-parameter programming techniques into a general framework of two-stage stochastic programming. The proposed approach provides a linkage to pre-defined management policies, deals with capacity-expansion planning issues, and reflects various uncertainties expressed as probability distributions and discrete intervals for a flood management system. Penalties are imposed when the policies are violated. The marginal costs are determined based on dual formulation of the ITIP model, and their effects on the optimal solutions are investigated. The developed model is applied to a case study of flood management. The solutions of binary variables represent the decisions of flood-diversion–capacity expansion within a multi-region, multi-flow-level, and multi-option context. The solutions of continuous variables are related to decisions of flood diversion toward different regions. The solutions of dual variables indicate the decisions of marginal costs associated with the resources of regions’ capacity, water availability, and allowable diversions. The results show that the proposed approach could obtain reliable solutions and adequately support decision making in flood management. 相似文献
2.
Managing water resources system in a mixed inexact environment using superiority and inferiority measures 总被引:1,自引:1,他引:0
Y. Lv G. H. Huang Y. P. Li W. Sun 《Stochastic Environmental Research and Risk Assessment (SERRA)》2012,26(5):681-693
A superiority–inferiority-based fuzzy-stochastic integer programming (SI-FSIP) method is developed for water resources management under uncertainty. In the SI-FSIP method, techniques of fuzzy mathematical programming with the superiority and inferiority measures and joint chance-constrained programming are integrated into an inexact mixed integer linear programming framework. The SI-FSIP improves upon conventional inexact fuzzy programming by directly reflecting the relationships among fuzzy coefficients in both the objective function and constraints with a high computational efficiency, and by comprehensively examining the risk of violating joint probabilistic constraints. The developed method is applied to a case study of water resources planning and flood control within a multi-stream and multi-reservoir context, where several studied cases (including policy scenarios) associated with different joint and individual probabilities are investigated. Reasonable solutions including binary and continuous decision variables are generated for identifying optimal strategies for water allocation, flood diversion and capacity expansion; the tradeoffs between total benefit and system-disruption risk are also analyzed. As the first attempt for planning such a water-resources system through the SI-FSIP method, it has potential to be applied to many other environmental management problems. 相似文献
3.
Two-stage fuzzy chance-constrained programming: application to water resources management under dual uncertainties 总被引:7,自引:7,他引:0
P. Guo G. H. Huang 《Stochastic Environmental Research and Risk Assessment (SERRA)》2009,23(3):349-359
In this study, a two-stage fuzzy chance-constrained programming (TFCCP) approach is developed for water resources management
under dual uncertainties. The concept of distribution with fuzzy probability (DFP) is presented as an extended form for expressing
uncertainties. It is expressed as dual uncertainties with both stochastic and fuzzy characteristics. As an improvement upon
the conventional inexact linear programming for handling uncertainties in the objective function and constraints, TFCCP has
advantages in uncertainty reflection and policy analysis, especially when the input parameters are provided as fuzzy sets,
probability distributions and DFPs. TFCCP integrates the two-stage stochastic programming (TSP) and fuzzy chance-constrained
programming within a general optimization framework. TFCCP incorporates the pre-regulated water resources management policies
directly into its optimization process to analyze various policy scenarios; each scenario has different economic penalty when
the promised amounts are not delivered. TFCCP is applied to a water resources management system with three users. Solutions
from TFCCP provide desired water allocation patterns, which maximize both the system’s benefits and feasibility. The results
indicate that reasonable solutions were generated for objective function values and decision variables, thus a number of decision
alternatives can be generated under different levels of stream flows, α-cut levels and fuzzy dominance indices. 相似文献
4.
Inexact two-stage stochastic partial programming: application to water resources management under uncertainty 总被引:5,自引:5,他引:0
Y. R. Fan G. H. Huang P. Guo A. L. Yang 《Stochastic Environmental Research and Risk Assessment (SERRA)》2012,26(2):281-293
In this study, an inexact two-stage stochastic partial programming (ITSPP) method is developed for tackling uncertainties
presented as intervals and partial probability distributions. A scenario-based interactive algorithm is proposed to solve
the ITSPP model. This algorithm is implemented through: (i) obtaining extreme points of the linear partial information (LPI);
(ii) generating an inexact two-stage stochastic programming (ITSP) model under each extreme point; (iii) solving ITSP models
through interactive algorithm proposed by Huang and Loucks (Civil Eng Environ Syst 17:95–118, 2000); (iv) acquiring the interval solutions under each extreme point and the final optimal interval for the objective function.
The developed method is applied to a case study for water-resources planning. The modelling results can generate a series
of decision alternatives under various system conditions, and thus help decision makers identify the desired water-resources
management policies under uncertainty. 相似文献
5.
Optimization of the industrial structure facing sustainable development in resource-based city subjected to water resources under uncertainty 总被引:2,自引:2,他引:0
J. J. Gu P. Guo G. H. Huang N. Shen 《Stochastic Environmental Research and Risk Assessment (SERRA)》2013,27(3):659-673
An inexact stochastic fuzzy programming (ISFP) approach has been developed for the optimization of the industrial structure in resource-based city subjected to water resources under uncertainty in present study. The ISFP method incorporates the techniques of inexact stochastic programming and inexact fuzzy chance-constrained programming, where the uncertainties are expressed as interval, fuzzy sets, and probability distribution, respectively. Moreover, it can also examine the risk of violating fuzzy tolerance constraints. The developed method is subsequently employed in a realistic case for industrial development in the Jinchang city, Gansu province, China. The result can help to analyze whether the water resources carrying capacity of Jinchang can meet the need of local economic development plan under uncertainty and help decision maker to optimize the industry structure under water resource constraints to meet the maximum economic efficiency. 相似文献
6.
Y. P. Cai G. H. Huang X. Wang G. C. Li Q. Tan 《Stochastic Environmental Research and Risk Assessment (SERRA)》2011,25(5):721-735
This paper presents the development and the first application of an inexact quadratic programming (IQP) approach for sustainable
water supply under multiple uncertainties. The developed IQP improves conventional nonlinear programming by tackling multiple
uncertainties within an individual parameter; IQP is also superior to existing inexact methods due to its reflection of economies
of scale and reduction of computational requirements. An interactive solution algorithm with high computational efficiency
was also proposed. The application of IQP to long-term planning of a multi-source multi-sector water supply system demonstrated
its applicability. The close reflection of system complexities, such as multiple uncertainties, scale economies and dynamic
parameters, could enhance the robustness of the optimization process as well as the acceptability of obtained results. Corresponding
to varied system conditions and decision priorities, the interval solutions from IQP could help generate a series of long-term
water supply strategies under a number of economic, environmental, ecological, and water-security targets. 相似文献
7.
This study presents a factorial two-stage stochastic programming (FTSP) approach for supporting water resource management
under uncertainty. FTSP is developed through the integration of factorial analysis and two-stage stochastic programming (TSP)
methods into a general modeling framework. It can handle uncertainties expressed as probability distributions and interval
numbers. This approach has two advantages in comparison to conventional inexact TSP methods. Firstly, FTSP inherits merits
of conventional inexact two-stage optimization approaches. Secondly, it can provide detailed effects of uncertain parameters
and their interactions on the system performance. The developed FTSP method is applied to a hypothetical case study of water
resources systems analysis. The results indicate that significant factors and their interactions can be identified. They can
be further analyzed for generating water allocation decision alternatives in municipal, industrial and agricultural sectors.
Reasonable water allocation schemes can thus be formulated based on the resulting information of detailed effects from various
impact factors and their interactions. Consequently, maximized net system benefit can be achieved. 相似文献
8.
Yao Ji Guohe Huang Wei Sun Yanfeng Li 《Stochastic Environmental Research and Risk Assessment (SERRA)》2016,30(2):621-633
Water quality management is a significant item in the sustainable development of wetland system, since the environmental influences from the economic development are becoming more and more obvious. In this study, an inexact left-hand-side chance-constrained fuzzy multi-objective programming (ILCFMOP) approach was proposed and applied to water quality management in a wetland system to analyze the tradeoffs among multiple objectives of total net benefit, water quality, water resource utilization and water treatment cost. The ILCFMOP integrates interval programming, left-hand-side chance-constrained programming, and fuzzy multi-objective programming within an optimization framework. It can both handle multiple objectives and quantify multiple uncertainties, including fuzziness (aspiration level of objectives), randomness (pollutant release limitation), and interval parameters (e.g. water resources, and wastewater treatment costs). A representative water pollution control case study in a wetland system is employed for demonstration. The optimal schemes were analyzed under scenarios at different probabilities (p i , denotes the admissible probability of violating the constraint i). The optimal solutions indicated that, most of the objectives would decrease with increasing probability levels from scenarios 1 to 3, since a higher constraint satisfaction probability would lead to stricter decision scopes. This study is the first application of the ILCFMOP model to water quality management in a wetland system, which indicates that it is applicable to other environmental problems under uncertainties. 相似文献
9.
Identification of optimal plans for municipal solid waste management in an environment of fuzziness and two-layer randomness 总被引:2,自引:2,他引:0
Q. Tan G. H. Huang Y. P. Cai 《Stochastic Environmental Research and Risk Assessment (SERRA)》2010,24(1):147-164
A superiority-inferiority-based inexact fuzzy-stochastic chance-constrained programming (SI-IFSCCP) approach is developed
for supporting long-term municipal solid waste management under uncertainty. Through SI-IFSCCP, multiple uncertainties expressed
as intervals, possibilistic and probabilistic distributions, as well as their combinations, could be directly communicated
into the optimization process, leading to enhanced system robustness. Through tackling fuzziness and two-layer randomness,
various subjective judgments of many stakeholders with different interests and preferences could be extensively reflected,
guaranteeing a lower degree of biases during data sampling and a higher degree of public acceptance for the generated plans.
Two levels of system-violation risk could also be reflected by SI-IFSCCP, reflecting the relationship between economic efficiency
and system reliability. A two-step solution method with improved computational efficiency is proposed for SI-IFSCCP. To demonstrate
its applicability, the developed methodology is then applied to a long-term municipal solid waste management problem. Useful
solutions have been generated. Satisfactory waste flow plans could be identified according to system conditions and policy
inclination, supporting in-depth tradeoff analyses between system optimality and reliability as well as between economic and
environmental objectives. 相似文献
10.
An inexact double-sided fuzzy chance-constrained programming (IDFCCP) method was developed in this study and applied to an agricultural effluent control management problem. IDFCCP was formulated through incorporating interval linear programming (ILP) into a double-sided fuzzy chance-constrained programming (DFCCP) framework, and could be used to deal with uncertainties expressed as not only possibility distributions associated with both left- and right-hand-side components of constraints but also discrete intervals in the objective function. The study results indicated that IDFCCP allowed violation of system constraints at specified confidence levels, where each confidence level consisted of two reliability scenarios. This could lead to model solutions with high system benefits under acceptable risk magnitudes. Furthermore, the introduction of ILP allowed uncertain information presented as discrete intervals to be communicated into the optimization process, such that a variety of decision alternatives can be generated by adjusting the decision-variable values within their intervals. The proposed model could help decision makers establish various production patterns with cost-effective water quality management schemes under complex uncertainties, and gain in-depth insights into the trade-offs between system economy and reliability. 相似文献
11.
Y. Xu L. G. Shao G. H. Huang 《Stochastic Environmental Research and Risk Assessment (SERRA)》2013,27(8):1929-1946
An inexact fuzzy-random-chance-constrained programming model (IFRCCMM) was developed for supporting regional air quality management under uncertainty. IFRCCMM was formulated through integrating interval linear programming within fuzzy-random-chance-constrained programming framework. It could deal with parameter uncertainties expressed as not only fuzzy random variables but also discrete intervals. Based on the stochastic and fuzzy chance-constrained programming algorithms, IFRCCMM was solved when constraints was satisfied under different satisfaction and violation levels of constraints, leading to interval solutions with different risk and cost implications. The proposed model was applied to a regional air quality management problem for demonstration. The obtained results indicated that the proposed model could effectively reflect uncertain components within air quality management system through employing multiple uncertainty-characterization techniques (in random, fuzzy and interval forms), and help decision makers analyze trade-offs between system economy and reliability. In fact, many types of solutions (i.e. conservative solutions with lower risks and optimistic solutions with higher risks) provided by IFRCCMM were suitable for local decision makers to make more applicable decision schemes according to their understanding and preference about the risk and economy. In addition, the modeling philosophy is general and applicable to many other environmental problems that may be complicated with multiple forms of uncertainties. 相似文献
12.
Inexact fuzzy two-stage programming for water resources management in an environment of fuzziness and randomness 总被引:1,自引:1,他引:0
Qing Hu Guohe Huang Zhenfang Liu Yurui Fan Wei Li 《Stochastic Environmental Research and Risk Assessment (SERRA)》2012,26(2):261-280
A standard lower-side attainment values based inexact fuzzy two-stage programming (SLA-IFTSP) approach is proposed for supporting
multi-water resources management under multi-uncertainties. The method improves upon the existing inexact two-stage stochastic
programming by the introduction of a standard average lower-side attainment values based fuzzy linear programming. Multi-uncertainties
such as intervals, probabilistic and/or possibilistic distributions and their combinations in water resources management can
be directly communicated into the water allocation process. The risk of infeasibility caused by the random water availabilities
can be analyzed by imposing economic penalties when the designed water allocations would not be satisfied after the occurrence
of random seasonal flows. Based on the standard average lower-side attainment index, the fuzzy random relationships representing
various subjective judgments in the model can be transformed into corresponding deterministic ones without additional constraints,
and thus guarantee a higher computational efficiency. A hypothetical case regarding two-source water resources management
is adopted for demonstrating its applicability. Reasonable solutions have been generated. They provide desired water allocations
with maximized system benefit under different water availability levels. The solutions of intervals with different probabilities
can be used for generating decision alternatives. Comparisons between the solutions from SLA-IFTSP and those from ITSP are
also undertaken. They show that SLA-IFTSP can generate more reasonable water allocation patterns with higher net system benefits
than ITSP. 相似文献
13.
C. Xu Y. P. Li G. H. Huang Y. Zhou 《Stochastic Environmental Research and Risk Assessment (SERRA)》2014,28(6):1613-1627
In this study, a fuzzy-queue (FQ)-based inexact stochastic quadratic programming (SQP) method is developed through coupling FQ technique with inexact SQP. FQ-SQP improves upon the existing stochastic programming methods by considering the effects of queuing phenomenon during the water resources allocation process. FQ-SQP cannot only handle uncertainties expressed as interval values, random variables, and fuzzy sets, but also tackle nonlinearity in the objective function; more importantly, it can reflect the effects of FQ on water resources allocation and system benefit. The FQ-SQP model is applied to a case study of planning water resources management, where FM/FM/1 (fuzzy exponential interarrival time, fuzzy exponential service time, and one server) queue is incorporated within the SQP modeling framework. Based on α-cut analysis technique, interval solutions with fuzzy arrival and service rates have been generated, which result in different water resources allocation patterns as well as changed waiting water amounts and system benefits. Results indicate that consideration of queuing problem impacts on water resources allocation can provide more useful information for decision makers and gain in-depth insights into the effects of queuing problems for water resources allocation. 相似文献
14.
An inexact inventory-theory-based chance-constrained programming model for solid waste management 总被引:1,自引:1,他引:0
XiuJuan Chen GuoHe Huang MeiQin Suo Hua Zhu Cong Dong 《Stochastic Environmental Research and Risk Assessment (SERRA)》2014,28(8):1939-1955
In this study, an inexact inventory-theory-based chance-constrained programming (IICP) model is proposed for planning waste management systems. The IICP model is derived through introducing inventory theory model into a general inexact chance-constrained programming framework. It can not only tackle uncertainties presented as both probability distributions and discrete intervals, but also reflect the influence of inventory problem in decision-making problems. The developed method is applied to a case study of long-term municipal solid waste (MSW) management planning. Solutions of total waste allocation, waste allocation batch and waste transferring period associated different risk levels of constraint violation are obtained. The results can be used to identify inventory-based MSW management planning with minimum system cost under various constraint-violation risks. Compared with the ICP model, the developed IICP model can more actually reflect the complexity of MSW management systems and provide more useful information for decision makers. 相似文献
15.
An interval-parameter multi-stage stochastic programming model for water resources management under uncertainty 总被引:1,自引:0,他引:1
In this study, an interval-parameter multi-stage stochastic linear programming (IMSLP) method has been developed for water resources decision making under uncertainty. The IMSLP is a hybrid methodology of inexact optimization and multi-stage stochastic programming. It has three major advantages in comparison to the other optimization techniques. Firstly, it extends upon the existing multi-stage stochastic programming method by allowing uncertainties expressed as probability density functions and discrete intervals to be effectively incorporated within the optimization framework. Secondly, 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. Thirdly, it cannot only handle uncertainties through constructing a set of scenarios that is representative for the universe of possible outcomes, but also reflect dynamic features of the system conditions through transactions at discrete points in time over the planning horizon. The developed IMSLP method is applied to a hypothetical case study of water resources management. The results are helpful for water resources managers in not only making decisions of water allocation but also gaining insight into the tradeoffs between environmental and economic objectives. 相似文献
16.
Y. L. Xie G. H. Huang 《Stochastic Environmental Research and Risk Assessment (SERRA)》2014,28(6):1555-1575
Water quality management along rivers involves making water-allocation plans, establishing water quality goals, and controlling pollutant discharges, which is complicated itself but further challenged by existence of uncertainties. In this study, an inexact two-stage stochastic downside risk-aversion programming (ITSDP) model is developed for supporting regional water resources allocation and water quality management problems under uncertainties. The ITSDP method is a hybrid of interval-parameter programming, two-stage stochastic programming, and downside risk measure to tackle uncertainties described in terms of interval values and probability distributions. A water quality simulation model was provided for reflecting the relationship between the water resources allocation, wastewater discharge, and environmental responses. The proposed approach was applied to a hypothetical case for a shared stream water quality management with one municipal, three industrial and two agricultural sectors. A number of scenarios corresponding to different river inflows and risk levels were examined. The results demonstrated that the model could effectively communicate the interval-format and random uncertainties, and risk-aversion into optimization process, and generate a trade-off between the system economy and stability. They could be helpful for seeking cost-effective management strategies under uncertainties, and gaining an in-depth insight into the water quality management system characteristics, and make cost-effective decisions. 相似文献
17.
Water resources systems are associated with a variety of complexities and uncertainties due to socio-economic and hydro-environmental impacts. Such complexities and uncertainties lead to challenges in evaluating the water resources management alternatives and the associated risks. In this study, the factorial analysis and fuzzy random value-at-risk are incorporated into a two-stage stochastic programming framework, leading to a factorial-based two-stage programming with fuzzy random value-at-risk (FTSPF). The proposed FTSPF approach aims to reveal the impacts of uncertainty parameters on water resources management strategies and the corresponding risks. In detail, fuzzy random value-at-risk is to reflect the potential risk about financial cost under dual uncertainties, while a multi-level factorial design approach is used to reveal the interaction between feasibility degrees and risk levels, as well as the relationships (including curvilinear relationship) between these factors and the responses. The application of water resources system planning makes it possible to balance the satisfaction of system benefit, the risk levels of penalty and the feasibility degrees of constraints. The results indicate that decision makers would pay more attention to the tradeoffs between the system benefit and feasibility degree, and the water allocation for agricultural section contributes most to control the financial loss of water. Moreover, FTSPF can generate a higher system benefit and more alternatives under various risk levels. Therefore, FTSPF could provide more useful information for enabling water managers to identify desired policies with maximized system benefit under different system-feasibility degrees and risk levels. 相似文献
18.
Y. Zhu Y. P. Li G. H. Huang L. Guo 《Stochastic Environmental Research and Risk Assessment (SERRA)》2013,27(3):693-704
In recent years, water shortages and unreliable water supplies have been considered as major barriers to agricultural irrigation water management in China, which are threatening human health, impairing prospects for agriculture and jeopardizing survival of ecosystems. Therefore, effective and efficient risk assessment of agricultural irrigation water management is desired. In this study, an inexact full-infinite two-stage stochastic programming (IFTSP) method is developed. It incorporates the concepts of interval-parameter programming and full-infinite programming within a two-stage stochastic programming framework. IFTSP can explicitly address uncertainties presented as crisp intervals, probability distributions and functional intervals. The developed model is then applied to Zhangweinan river basin for demonstrating its applicability. Results from the case study indicate that compromise solutions have been obtained. They provide the desired agricultural irrigation water-supply schemes, which are related to a variety of tradeoffs between conflicting economic benefits and associated penalties attributed to the violation of predefined policies. The solutions can be used for generating decision alternatives and thus help decision makers to identify desired agricultural irrigation targets with maximized system benefit and minimized system-failure risk. Decision makers can adjust the existing agricultural irrigation patterns, and coordinate the conflict interactions among economic benefit, system efficiency, and agricultural irrigation under uncertainty. 相似文献
19.
D. Z. Fu Y. P. Li G. H. Huang 《Stochastic Environmental Research and Risk Assessment (SERRA)》2012,26(3):375-391
In this study, a fuzzy-Markov-chain-based stochastic dynamic programming (FM-SDP) method is developed for tackling uncertainties
expressed as fuzzy sets and distributions with fuzzy probability (DFPs) in reservoir operation. The concept of DFPs used in
Markov chain is presented as an extended form for expressing uncertainties including both stochastic and fuzzy characteristics.
A fuzzy dominance index analysis approach is proposed for solving multiple fuzzy sets and DPFs in the proposed FM-SDP model.
Solutions under a set of α-cut levels and fuzzy dominance indices can be generated by solving a series of deterministic submodels.
The developed method is applied to a case study of a reservoir operation system. Solutions from FM-SDP provide a range of
desired water-release policies under various system conditions for reservoir operation decision makers, reflecting dynamic
and dual uncertain features of water availability simultaneously. The results indicate that the FM-SDP method could be applicable
to practical problems for decision makers to obtain insight regarding the tradeoffs between economic and system reliability
criteria. Willingness to obtain a lower benefit may guarantee meeting system-constraint demands; conversely, a desire to acquire
a higher benefit could run into a higher risk of violating system constraints. 相似文献
20.
ITOM: an interval-parameter two-stage optimization model for stochastic planning of water resources systems 总被引:3,自引:2,他引:3
Imran Maqsood Guohe Huang Yuefei Huang Bing Chen 《Stochastic Environmental Research and Risk Assessment (SERRA)》2005,19(2):125-133
Planning of water resources systems is often associated with many uncertain parameters and their interrelationships are complicated. Stochastic planning of water resources systems is vital under changing climate and increasing water scarcity. This study proposes an interval-parameter two-stage optimization model (ITOM) for water resources planning in an agricultural system under uncertainty. Compared with other optimization techniques, the proposed modeling approach offers two advantages: first, it provides a linkage to pre-defined water policies, and; second, it reflects uncertainties expressed as probability distributions and discrete intervals. The ITOM is applied to a case study of irrigation planning. Reasonable solutions are obtained, and a variety of decision alternatives are generated under different combinations of water shortages. It provides desired water-allocation patterns with respect to maximum system benefits and highest feasibility. Moreover, the modeling results indicate that an optimistic water policy corresponding to higher agricultural income may be subject to a higher risk of system-failure penalties; while, a too conservative policy may lead to wastage of irrigation supplies. 相似文献