Water quality management in a wetland system using an inexact left-hand-side chance-constrained fuzzy multi-objective approach

Ji, Yao; Huang, Guohe; Sun, Wei; Li, Yanfeng

doi:10.1007/s00477-015-1094-5

Cited by 11 publications

(3 citation statements)

References 24 publications

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“…e researchers proposed a multicriteria plausibility framework model for the investment rebalancing problem, in which return, risk, and liquidity are represented by fuzzy parameters, respectively [22]. e researchers combined fuzzy theory with portfolio matrices, and the proposed model construction method is able to accurately describe investors' subjective preferences [23][24][25][26]. Using a single-input type fuzzy inference method, the researchers investigated the robust stochastic fuzzy MV-based portfolio selection problem [27].…”

Section: Related Workmentioning

confidence: 99%

[Retracted] Application of Algorithms of Constrained Fuzzy Models in Economic Management

Meng

Zhu

2021

Complexity

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Stochasticity and ambiguity are two aspects of uncertainty in economic problems. In the case of investments in risky assets, this uncertainty is manifested in the uncertainty of future returns. On the contrary, the complexity of the economic phenomenon itself and the ambiguity inherent in human thinking and judgment are characterized by indistinct boundaries. For the same problem, research from different perspectives can often provide us with more comprehensive and systematic information. Currently, the expected value of return or the variance representing risk is still used as a rational investment criterion for both single-stage portfolios and multistage portfolios. However, in general, the greater the expected return of an investor, the greater the risk he should take. Different investors have different requirements for profitability, but regardless of their expected return, they always hope to find a set of portfolios that maximize the probability of achieving the expected rate of return. In this paper, after analyzing the development of portfolio investment theory research, we take fuzzy information processing as the entry point and systematically discuss the theory and methods of fuzzy modeling of portfolio investment decision-making from the perspective of fuzziness around the portfolio investment decision-making process. The results of the empirical analysis show that the existence of basis constraints affects investors’ investment strategies as well as their final returns, but there is a limit to the influence of basis constraints on portfolio performance, and investors can obtain optimal investment returns by selecting a reasonable number of securities to form a portfolio based on the characteristics of different securities.

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Section: Related Workmentioning

confidence: 99%

[Retracted] Application of Algorithms of Constrained Fuzzy Models in Economic Management

Meng

Zhu

2021

Complexity

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“…For example, pollutant discharge allowances are often affected by pollutant discharge rates (which influenced by random events such as temperature and precipitation) and decision makers' estimations; the allowable loads are not measured with certainty but in fact represent a probability distribution. Consequently, a number of mathematical techniques were launched to examine economic, environmental and ecological impacts of alternative pollution control actions under uncertainty, and thus aid the decision makers in generating effective water pollution control plans and policies [8][9][10][11][12][13][14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

A Semi-Infinite Interval-Stochastic Risk Management Model for River Water Pollution Control under Uncertainty

Liu

Huang

et al. 2017

Water

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Abstract:In this study, a semi-infinite interval-stochastic risk management (SIRM) model is developed for river water pollution control, where various policy scenarios are explored in response to economic penalties due to randomness and functional intervals. SIRM can also control the variability of the recourse cost as well as capture the notion of risk in stochastic programming. Then, the SIRM model is applied to water pollution control of the Xiangxihe watershed. Tradeoffs between risks and benefits are evaluated, indicating any change in the targeted benefit and risk level would yield varied expected benefits. Results disclose that the uncertainty of system components and risk preference of decision makers have significant effects on the watershed's production generation pattern and pollutant control schemes as well as system benefit. Decision makers with risk-aversive attitude would accept a lower system benefit (with lower production level and pollutant discharge); a policy based on risk-neutral attitude would lead to a higher system benefit (with higher production level and pollutant discharge). The findings can facilitate the decision makers in identifying desired product generation plans in association with financial risk minimization and pollution mitigation.

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“…Tavakoli et al [17] developed an interactive two-stage stochastic fuzzy programming method to handle uncertainties expressed as fuzzy boundary intervals (i.e., the lowerand upper-bounds of intervals are presented as possibility distributions). Ji et al [18] enhanced an inexact left-hand-side chance-constrained fuzzy multi-objective programming approach to cope with fuzziness in the constraints and objectives. Generally, the conventional fuzzy programming methods could only tackle fuzzy uncertainty with precise membership grades, which may encounter difficulty when the membership grades are also obtained as fuzzy sets.…”

Section: Introductionmentioning

confidence: 99%

A Recourse-Based Type-2 Fuzzy Programming Method for Water Pollution Control under Uncertainty

Liu

Huang

et al. 2017

Symmetry

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Abstract:In this study, a recourse-based type-2 fuzzy programming (RTFP) method is developed for supporting water pollution control of basin systems under uncertainty. The RTFP method incorporates type-2 fuzzy programming (TFP) within a two-stage stochastic programming with recourse (TSP) framework to handle uncertainties expressed as type-2 fuzzy sets (i.e., a fuzzy set in which the membership function is also fuzzy) and probability distributions, as well as to reflect the trade-offs between conflicting economic benefits and penalties due to violated policies. The RTFP method is then applied to a real case of water pollution control in the Heshui River Basin (a rural area of China), where chemical oxygen demand (COD), total nitrogen (TN), total phosphorus (TP), and soil loss are selected as major indicators to identify the water pollution control strategies. Solutions of optimal production plans of economic activities under each probabilistic pollutant discharge allowance level and membership grades are obtained. The results are helpful for the authorities in exploring the trade-off between economic objective and pollutant discharge decision-making based on river water pollution control.

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Water quality management in a wetland system using an inexact left-hand-side chance-constrained fuzzy multi-objective approach

Cited by 11 publications

References 24 publications

[Retracted] Application of Algorithms of Constrained Fuzzy Models in Economic Management

[Retracted] Application of Algorithms of Constrained Fuzzy Models in Economic Management

A Semi-Infinite Interval-Stochastic Risk Management Model for River Water Pollution Control under Uncertainty

A Recourse-Based Type-2 Fuzzy Programming Method for Water Pollution Control under Uncertainty

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