Study Of Fuzzy Goal Programming Model To Production Planning Problems Approach

Vinsensia, Desi; Utami, Yulia

doi:10.35335/cit.vol13.2021.149.pp75-81

Cited by 3 publications

(3 citation statements)

References 23 publications

(21 reference statements)

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“…The GP model was enhanced using fuzzy set theory [22] to manage uncertainty data, resulting in FGP. The main goal is to improve the ability of FGP to deal with the nature of uncertainty when modeling problems [26,27]. Uncertainties are frequently related to the goal objectives in a case such as a production planning model.…”

Section: Fuzzy Goal Programming (Fgp)mentioning

confidence: 99%

“…To overcome uncertainties in multi-objective decision-making circumstances, FGP combines GP and fuzzy set theory [27]. It's acceptable to consider that the possible values of the model is features and coefficients are unknown and that the decision maker can offer them, or that these values can be found using historical data or statistical inference.…”

Section: Fuzzy Goal Programming (Fgp)mentioning

confidence: 99%

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Hybrid Uncertainty-Goal Programming Model with Scaled Index for Production Planning Assessment

Watada

Arbaiy

Chen³

2021

FinTech

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Goal programming (GP) can be thought of as an extension or generalization of linear programming to handle multiple, normally conflicting objective measures. Each of these measures is given a goal or target value to be achieved. Unwanted deviations from this set of target values are then minimized in an achievement function. Production planning is an important process that aims to leverage the resources available in industry to achieve one or more business goals. However, the production planning that typically uses mathematical models has its own challenges where parameter models are sometimes difficult to find easily and accurately. Data collected with various data collection methods and human experts’ judgments are often prone to uncertainties that can affect the information presented by quantitative results. This study focuses on resolving data uncertainties as well as multi-objective optimization using fuzzy random methods and GP in production planning problems. GP was enhanced with fuzzy random features. Scalable approaches and maximum minimum operators were then used to solve multi-object optimization problems. Scaled indices were also introduced to resolve fuzzy symbols containing unspecified relationships. The application results indicate that the proposed approach can mitigate the characteristics of uncertainty in the analysis and achieve a satisfactory optimized solution.

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Section: Fuzzy Goal Programming (Fgp)mentioning

confidence: 99%

Section: Fuzzy Goal Programming (Fgp)mentioning

confidence: 99%

Hybrid Uncertainty-Goal Programming Model with Scaled Index for Production Planning Assessment

Watada

Arbaiy

Chen³

2021

FinTech

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“…Silva et al (2020) optimized hydrogen networks using mathematical programming. Vinsensia et al (2021) formulated a fuzzy goal programming technique to optimize the production planning system with achieving different objectives simultaneously. Khalifa et al (2021a) demonstrated a novel approach for tackling quadratic fractional programming problems in a neutrosophic environment.…”

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confidence: 99%

Application of fuzzy goal programming approach in the real-life problem of agriculture sector

Malik

Kumar

Pathak

et al. 2023

BJO&PM

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Goal: The present study aimed to demonstrate the applicability of the fuzzy goal programming to frame the decision support system for the decision-makers to deal with the real-life problem of the agriculture sector namely the apple cultivation planning problem and to obtain an optimum solution. Design / Methodology / Approach: The proposed method occurred within the apple-producing sector in the Kashmir valley of India and included the collection of data through interviews and surveys with various farmers. Also, the results were drawn with the help of LINGO 18.0. Results: The current finding implies that all of the desired objectives have been met, as well as an optimal solution. The proposed model offers a significant approach for designing plans to determine various agricultural activities in a fuzzy decision environment. Finally, the current study conducts a case study in the apple cultivation sector to obtain various competing objectives. Sensitivity analysis was also performed on its preferential weight parameters. Limitations of the investigation: It should be noted that the parameters related to production cost, transportation cost, and cost of material may change over the years. The selling price may also vary according to the quality of apples and over the years. Because of natural factors, the annual production of apples may also vary. Practical implication: The current study shows that using fuzzy goal programming techniques in an apple production process has a huge potential to increase farmers' income. It can be concluded that the current study can help decision-makers to deal with real-life planning issues in the agricultural sector. Future research can also take advantage of other initiation strategies. Originality/Value: The study looks at the applicability of the fuzzy goal programming paradigm in a new field of apple production in the agriculture sector. According to our knowledge, this is the first time the optimization model has been used in the apple cultivation sector.

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Optimizing the Cropping Pattern in Nangarhar Province Based on the Perspective of Sustainable Agricultural Development: Fuzzy Goal Programming Approach

Rasikh,

Joolaie,

Keramatzadeh

et al. 2024

Process Integr Optim Sustain

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Study Of Fuzzy Goal Programming Model To Production Planning Problems Approach

Cited by 3 publications

References 23 publications

Hybrid Uncertainty-Goal Programming Model with Scaled Index for Production Planning Assessment

Hybrid Uncertainty-Goal Programming Model with Scaled Index for Production Planning Assessment

Application of fuzzy goal programming approach in the real-life problem of agriculture sector

Optimizing the Cropping Pattern in Nangarhar Province Based on the Perspective of Sustainable Agricultural Development: Fuzzy Goal Programming Approach

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