Interval-parameter Fuzzy-stochastic Semi-infinite Mixed-integer Linear Programming for Waste Management under Uncertainty

Guo, Ping; Huang, Guohe; He, Li; Li, H. L.

doi:10.1007/s10666-008-9143-9

Cited by 29 publications

(7 citation statements)

References 49 publications

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“…Lake water storage capacity is more than the lake effective capacity B for ecological sustainable development, but more lake water is often divided for greater benefits in the actual making-decision process, allowing the existence of appropriate risk p. The stochastic chance-constrained programming can effectively reflect the reliability of the system to meet the constraints (or risk) [42]. The model can effectively solve uncertainties, described as intervals and fuzzy characteristics, which exist in the water resources allocation process.…”

Section: (3) Lake Ecological Capacity Constraintsmentioning

confidence: 99%

Optimal Allocation Method of Irrigation Water from River and Lake by Considering the Field Water Cycle Process

Huo

2017

Water

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At present, the shortage of water resources has become a serious constraint to the further development of social economy. The optimal allocation of multi-water resources is valuable for agricultural water management in arid and semi-arid regions. However, traditional deterministic programming does not solve the complex water resources allocation in irrigation systems. Furthermore, previous allocation methods of irrigation water seldom considered the water cycle process, especially for multi-sources of irrigation. In this study, we develop an inexact fuzzy stochastic simulation-optimization programming (IFSSOP) model for the irrigation water optimal allocation of two water sources. The model combines the crop water model and the field water cycle model with an uncertainty optimization model, which considers the contribution of groundwater to crop water consumption. As a case study, the developed model is used in an arid area with two irrigation water sources: a river and a lake. Accordingly, the total optimal allocation irrigation water amounts of river and lake water under different violation probabilities in various hydrological years were obtained. By comparing the IFSSOP model with the IFSSOP model without considering the contribution of shallow groundwater (IFSSOP-NG model), it can be shown that the system benefits of the developed model are higher. With the lake water source from flood water, the region can save 30-34% of the river water, maintaining the original crop water deficit irrigation ratio. Consequently, application of the IFSSOP model in irrigation scheduling will provide effective water allocation patterns to save more water in an arid region with shallow groundwater.

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Section: (3) Lake Ecological Capacity Constraintsmentioning

confidence: 99%

Optimal Allocation Method of Irrigation Water from River and Lake by Considering the Field Water Cycle Process

Huo

2017

Water

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“…To achieve effective management of limited irrigation water resources, the decision makers often desire optimal allocation schemes to avoid high costs and large water consumptions, especially for the arid and semi-arid areas. Moreover, the decision makers need to consider the system fairness, balance the different-level preferences, and address interval uncertainties in practical problems [45][46][47]. To deal with these challenges of agricultural water resources management, an ILFBP model can be formulated as follows:…”

Section: The Ilfbp Model For Agricultural Water Resources Managementmentioning

confidence: 99%

An Optimization-Evaluation Agricultural Water Planning Approach Based on Interval Linear Fractional Bi-Level Programming and IAHP-TOPSIS

Zhang

Zhu

et al. 2019

Water

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In this study, an interval linear fractional bi-level programming (ILFBP) model was developed for managing irrigation-water resources under uncertainty. The ILFBP can fully address system fairness, uncertainties, and the leader–follower relationship of decision makers in the optimization process, which can better reflect the complexity of real decision-making process and help formulate reasonable water policies. An interactive fuzzy coordination algorithm based on satisfaction degree was introduced to solve the ILFBP model. In order to evaluate the applicability of optimization schemes, the interval analytic hierarchy process (IAHP) and the interval technique for order preference by similarity to an ideal solution (TOPSIS) method were integrated as IAHP-TOPSIS. To verify its validity, the developed optimization-evaluation framework was applied to an irrigation water management case study in the middle reaches of the Shiyang River Basin, located in the northwest China. The ILFBP model results show that the total water allocation is [6.73, 7.37] × 108 m3, saving nearly 0.9 × 108 m3 more than the current situation. The benefit per unit of water is [2.38, 2.95] yuan/m3, nearly 0.4 yuan/m3 more than the status quo, and the Gini coefficient is within a reasonable range of [0.35, 0.38]. The ILFBP model can well balance economic benefits and system fairness. Through the evaluation bases on IAHP-TOPSIS, the results of ILFBP show better water allocation effects and applicability than the other two models in this study area. Furthermore, due to various characteristics such as geographical location, population and area, there are three irrigation districts, Xiying, Donghe, and Qinghe, showing higher importance than others when considering regional water allocation. These findings can provide useful information for limited water resource managers and help decision makers determine effective alternatives of water resource planning under uncertainty.

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“…Also one may mention the fuzzy-stochastic programming approaches in [30], [13] and [32]. Nasseri et al in [26] presented a new method for solving FLP problem via FLSIP.…”

Section: Introductionmentioning

confidence: 99%

A hybrid method for solving fuzzy semi-infinite linear programming problems

Fakharzadeh

Khosravi

2015

Journal of Intelligent &Amp; Fuzzy Systems

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Abilities of fuzzy models in more adaptations with the real world phenomena causes that in this paper, we remodel semi-infinite linear programming problems as fuzzy problems which contained the crisp objective function and the infinite number of fuzzy constraints. Then, we introduce a new hybrid solution method for these fuzzy semi-infinite linear programming problems. This solution technique is a kind of cutting plane algorithm in which its sub-problems were solved by using the Zimmermannmethod. Convergence of the presented algorithm is proved, and some numerical test examples are given and also the obtained results are compared.

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Interval-parameter Fuzzy-stochastic Semi-infinite Mixed-integer Linear Programming for Waste Management under Uncertainty

Cited by 29 publications

References 49 publications

Optimal Allocation Method of Irrigation Water from River and Lake by Considering the Field Water Cycle Process

Optimal Allocation Method of Irrigation Water from River and Lake by Considering the Field Water Cycle Process

An Optimization-Evaluation Agricultural Water Planning Approach Based on Interval Linear Fractional Bi-Level Programming and IAHP-TOPSIS

A hybrid method for solving fuzzy semi-infinite linear programming problems

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