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Crop cultivation planning with fuzzy estimation using water wave optimization.

Li-Chang Liu1, Kang-Cong Lv1, Yu-Jun Zheng1

  • 1School of Information Science and Technology, Hangzhou Normal University, Hangzhou, Zhejiang, China.

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Summary
This summary is machine-generated.

This study introduces a fuzzy optimization approach for crop cultivation planning, using water wave optimization (WWO) to manage uncertain factors like cost and price. The method significantly boosts profits compared to traditional approaches.

Keywords:
crop cultivation planningevolutionary algorithmsfuzzy parametersoptimizationwater wave optimization (WWO).

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Area of Science:

  • Agricultural Economics
  • Operations Research
  • Fuzzy Systems

Background:

  • Crop cultivation planning is complex due to uncertain economic factors (cost, yield, price).
  • Traditional exact programming methods are impractical for these uncertain conditions.
  • Fuzzy parameters offer a way to model and manage uncertainty in agricultural management.

Purpose of the Study:

  • To develop a robust crop cultivation planning model addressing uncertain factors.
  • To adapt and apply the water wave optimization (WWO) algorithm for fuzzy optimization in agriculture.
  • To enhance total profit maximization in cultivation management under uncertainty.

Main Methods:

  • Formulating crop cultivation planning as a problem with fuzzy parameters.
  • Utilizing the water wave optimization (WWO) algorithm, an efficient evolutionary approach.
  • Evaluating solutions using expected, optimistic, and pessimistic values for robust decision-making.

Main Results:

  • The fuzzy optimization approach, using WWO, effectively handles uncertain factors in crop planning.
  • Solutions were evaluated based on a combination of expected, optimistic, and pessimistic values.
  • Test results in East China demonstrated significantly higher profits than non-fuzzy methods.

Conclusions:

  • Fuzzy optimization with WWO provides a credible and effective solution for crop cultivation planning under uncertainty.
  • This approach leads to superior profit maximization compared to methods relying solely on expected values.
  • The study highlights the practical applicability of fuzzy optimization in complex agricultural management.