Fuzzy multi-objective linear programming applying to crop area planning

Zeng, Xin‐An; Kang, Shaozhong; Li, Fusheng; Zhang, Lu; Guo, Ping

doi:10.1016/j.agwat.2010.08.010

Cited by 112 publications

(38 citation statements)

References 25 publications

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“…Such articulation of preferences and priorities are uncertain in nature without precise boundaries, which can usually be modeled as fuzzy membership grades. As well, many parameters which are of significance for the success of modeling efforts, such as crop water demand and water availability, are hard to be known as deterministic values due to natural variability and measuring limitations [22][23][24][25][26]. The incapability of previous multi-objective programming models in reflecting uncertainties would lead to significant risks of system violation.…”

Section: Introductionmentioning

confidence: 99%

Optimal Use of Agricultural Water and Land Resources through Reconfiguring Crop Planting Structure under Socioeconomic and Ecological Objectives

Tan

Shan

2017

Water

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Many economic, social and ecological problems can be attributed to the scarcity and mismanagement of water and land resources. In this study, a multi-objective fuzzy-robust programming (MOFRP) method was developed for supporting the optimal use of land and water resources in agriculture. MOFRP improved existing methods through taking ecological services of crop cultivation into account. It was also capable of reflecting fuzziness in preferences, priorities and parameters that were largely neglected in previous agricultural decision making. This method was applied to address a case in arid northwestern China. Optimal plans of crop cultivation reconfiguration were generated for sustaining local development under economic, ecological and social objectives as well as physical restraints in water and land resources. Compared to the status quo, the optimized plan would increase economic and ecological benefits by 12.2% and 18.8%, respectively. The efficiency of irrigation water could also be enhanced with the economic and ecological benefits per unit water being raised and the water consumption per unit land being reduced. The comparisons of the MOFRP model to four alternatives validated that it was capable of achieving satisfactory benefits and reducing system-violation risks without neglecting valuable uncertain information and ecological services of crops. The proposed method was also applicable to other multi-objective management problems under uncertainty without loss of generality.

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Section: Introductionmentioning

confidence: 99%

Optimal Use of Agricultural Water and Land Resources through Reconfiguring Crop Planting Structure under Socioeconomic and Ecological Objectives

Tan

Shan

2017

Water

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“…However, it is sometimes difficult to definitely estimate the exact values of the profit and the working time in crop planning problems because of lack of data and/or some factors such as human skills. Zeng et al [50] considered a fuzzy multi-objective programming approach to a crop planning problem. In this section, we apply the proposed model to solve a crop planning problem in a fuzzy stochastic environment where the profit and the working times are given as discrete fuzzy random variables.…”

Section: Numerical Experimentsmentioning

confidence: 99%

Possibility/Necessity-Based Probabilistic Expectation Models for Linear Programming Problems with Discrete Fuzzy Random Variables

2017

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This paper considers linear programming problems (LPPs) where the objective functions involve discrete fuzzy random variables (fuzzy set-valued discrete random variables). New decision making models, which are useful in fuzzy stochastic environments, are proposed based on both possibility theory and probability theory. In multi-objective cases, Pareto optimal solutions of the proposed models are newly defined. Computational algorithms for obtaining the Pareto optimal solutions of the proposed models are provided. It is shown that problems involving discrete fuzzy random variables can be transformed into deterministic nonlinear mathematical programming problems which can be solved through a conventional mathematical programming solver under practically reasonable assumptions. A numerical example of agriculture production problems is given to demonstrate the applicability of the proposed models to real-world problems in fuzzy stochastic environments.

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“…The total net profit target had increased 11.25%, while the total soil loss and crop water consumption, the minimum target, had decreased to about 19.45% and 11.79% respectively. Zeng et al (2010) employed FMOLP to optimize crop area with the model coefficients estimated from experiment data. The results showed that yield and net return increased when irrigation area and evapotranspiration increased.…”

Section: The Changing Of Fmolp Target Valuesmentioning

confidence: 99%

“…the agricultural statistics determine the DVCs on crop yield, the universal soil loss equation (USLE) usage which estimates the DVCs for the rate of soil erosion (Makowski, 2003;Sadeghi et al, 2009). However, some coefficients cannot be defined precisely due to variation of information and uncertainty (Zeng et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

Reevaluating FMOLP Decision Variable Coefficients Using the SWAT Results for the Optimization of Sustainable Agricultural Land Use in Small Watershed

Mahaarcha¹,

Tangtham²

2013

MAS

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The inappropriate use of agricultural land has caused several environmental and socio-economic problems. Fuzzy multiple objectives linear programming (FMOLP) is a mathematical technique that can be effective in land use planning. It requires decision variable coefficients (DVCs) to formulate the problem model covering all environmental and socio-economic aspects. The solution from a formulated FMOLP model provides optimal land use proportion and then the proportion is relocated t o produce the land use planning map. The map is then transferred to the soil and water assessment tools (SWAT) for assessing the impacts. The SWAT results give out a value which differs from the initial DVCs in the comparable aspects. This difference indicates that the initial DVCs were not realistic for the selected watershed and the land use planning map were not optimal.This study attempts to reevaluate DVCs in the FMOLP model by designing a method of sustainable agricultural land-use planning which makes use of the outputted results from the SWAT model. The results in terms of soil loss, crop water consumption, crop yields and net profit are simulated by SWAT and then replace to the DVC's value. This procedure will be repeated until a small difference between SWAT results and DVC's values are obtained. The findings of this study show that the final land use map achieves a higher target value than the map that was constructed after the initial phase of testing in all of objective. It is hoped the outcomes of this loop back process can be linked to the optimizing technique, so that environmental models can be utilized in the model output to improve optimum proportional solutions in any decision support system (DSS) for future sustainable agricultural land use planning.

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Fuzzy multi-objective linear programming applying to crop area planning

Cited by 112 publications

References 25 publications

Optimal Use of Agricultural Water and Land Resources through Reconfiguring Crop Planting Structure under Socioeconomic and Ecological Objectives

Optimal Use of Agricultural Water and Land Resources through Reconfiguring Crop Planting Structure under Socioeconomic and Ecological Objectives

Possibility/Necessity-Based Probabilistic Expectation Models for Linear Programming Problems with Discrete Fuzzy Random Variables

Reevaluating FMOLP Decision Variable Coefficients Using the SWAT Results for the Optimization of Sustainable Agricultural Land Use in Small Watershed

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