An inexact stochastic optimization model for agricultural irrigation management with a case study in China

Li, Xiaoyan; Lu, Hongwei; He, Li; Shi, Bin

doi:10.1007/s00477-013-0748-4

Cited by 20 publications

(13 citation statements)

References 38 publications

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“…Indeed, there is a stream of works dealing with waste management under uncertainty where the uncertain LP problem is solved through its reformulation as an LSIO problem. This approach is compared with the interval linear optimization one in [105], [110], [111], [114], [134], [147] (a paper on water resources management), whose authors conclude that the LSIO approach has the following advantages: (i) It re ‡ects better the association of the total system revenue with gas and power prices; (ii) it generates more reliable solutions with a lower risk of system failure due to the possible constraints violation; and (iii) it provides a more ‡exible management strategy since the capital availability can be adjusted with the variations in gas prices. An integer LSIO model has been proposed in [196] for planning municipal energy systems.…”

Section: Robust Linear and Convex Programmingmentioning

confidence: 99%

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Recent contributions to linear semi-infinite optimization

Goberna

López

2017

4OR-Q J Oper Res

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This paper reviews the state-of-the-art in the theory of deterministic and uncertain linear semi-in…nite optimization, presents some numerical approaches to this type of problems, and describes a selection of recent applications in a variety of …elds. Extensions to related optimization areas, as convex semi-in…nite optimization, linear in…nite optimization, and multi-objective linear semi-in…nite optimization, are also commented.

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Section: Robust Linear and Convex Programmingmentioning

confidence: 99%

“…Selected applications of LSIO to di¤erent …elds can be found in [3], [4], [19], [20], [21], [49], [56], [69], [115], [117], [119], [120], [134], [140], [159], [164], [168], [180], [179], [191], [192] and [196].…”

Section: -Other Referencesmentioning

confidence: 99%

Recent contributions to linear semi-infinite optimization

Goberna

López

2017

4OR-Q J Oper Res

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“…Previously, a significant number of optimization techniques were developed for dealing with environmental management problems, including stochastic mathematical programming (SMP), fuzzy mathematical programming (FMP) and interval mathematical programming (IMP), as well as their integrations (Macchiato et al 1994;Teng and Tzeng 1994;Lejano et al 1997;Liu et al 2003;Zhu et al 2009;Cao et al 2010;Qin et al 2010;Xu et al 2010a;Fan et al 2012;Hu et al 2012;lv et al 2012;Xu et al 2012;Li et al 2014). For example, Liu et al (2003) developed a hybrid fuzzy-stochastic robust programming method for regional air quality management where the random and fuzzy variables are tackled by stochastic chance-constrained programming and fuzzy robust programming, respectively.…”

Section: Introductionmentioning

confidence: 99%

Mathematical modeling for air quality management under stochastic and interval uncertainties

Liu

Wen

Zheng

2014

Stoch Environ Res Risk Assess

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In this study, an inexact stochastic robust air quality management model (ISRAQMM) was developed for supporting regional air pollution control. The Fengrun district in Tangshan City, China, was used as a study case for demonstration. The ISRAQMM has the advantages of reflecting uncertainty and evaluating trade-offs between system economy and reliability, where the model parameters are provided as discrete intervals and deterministic values under various scenarios. The model's objective function was an integration of the expected cost, cost variability and penalty function of constraints violation rather than the traditional objective function considering only the economic factor; meanwhile, the inexact model parameters were expressed as discrete intervals, which have low data requirements. A variety of solutions were obtained, which could be used to help evaluate the trade-off between system economy and reliability. Using the case study, the applicability of the ISRAQMM was demonstrated. A set of conservative solutions with lower risks and cost-effective solutions with higher risks was provided. The balanced scenario solution was recommended for decision makers, since it respects both system economy and reliability. The successful applications of the ISRAQMM in the studied real world are expected to be a good demonstration for many other areas.

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“…A possible application of simulation in conjunction with linear programming is shown to maximize the nutrient contents of compost manure prepared using pig dung, buffalo dung, green manure and concentrated super phosphate in (Minh, Ranamukhaarachchi & Jayasuriya, 2007). Simulation and linear programming are also applied in soil erosion control (Segarra, Kramer & Taylor, 1985), irrigation management (Li, Lu, He and Shi, 2014) and urban water management (Zhu, Marques & Lund, 2005), working schedule planning (Matsui, Inoue, Matsushita, Yamada, Yamamoto & Sumigama, 2005), organic farming risk management (Lauwers, Decock, Dewit & Wauters, 2010), etc.…”

Section: Introductionmentioning

confidence: 99%

Analyzing the value of the residue of crops grown on arable land with stochastic optimization

Zlatniczki

2015

JAI

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A B S T R A C TDetermining the value of the residues of crops grown on arable land is a non-trivial task, depending much on how it is defined. In this paper the value of residues is considered to be the savings achieved on the total expense of artificial fertilizer distribution by returning the residues into the soil. A general linear programming approach is presented to obtain optimal artificial fertilizer allocation. Since the amount of artificial fertilizers required depends on uncertain inputs Monte Carlo simulation is applied in conjunction with linear programming to solve the arising stochastic optimization problem. The input data, such as the national average yield, specific amounts of nutrients required by crops to achieve the national average yield and publicly available details of different artificial fertilizer products are specific to Hungary, but the mathematical model presented is general in nature. Simulations are executed for some of the major crops, including wheat, corn, sunflower and rape. The distribution of savings achieved on returning their residues to the soil is provided at the end of the paper for further use.

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An inexact stochastic optimization model for agricultural irrigation management with a case study in China

Cited by 20 publications

References 38 publications

Recent contributions to linear semi-infinite optimization

Recent contributions to linear semi-infinite optimization

Mathematical modeling for air quality management under stochastic and interval uncertainties

Analyzing the value of the residue of crops grown on arable land with stochastic optimization

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