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<p>This paper presents a new model of production planning in rainbow trout aquaculture that aims at improving resource usage and enhancing decision-making accuracy in an effort to reduce costs and provide methods for application when dealing with uncertainty. The model caters for such operational issues as right juvenile fish purchases, fish growth rates, and the right time to harvest the fishes given capacities and mortality rate. Using a case study in Iran, both deterministic and uncertain conditions were employed in the implementation of the model, to gain a better understanding of how the production can be optimized in order to have the least cost and the highest profit rate. The paper showed the application potential of the model for fish farm managers by providing strategic insights and tools for cost minimization and risk management in an uncertain environment. The study emphasizes optimizing fish growth rates, mortality, and harvesting within fishpond capacity and market demand constraints. The findings revealed that incorporating uncertainty led to a cost increase of 20%, demonstrating the model’s resilience and applicability. Sensitivity analyses highlighted demand, growth, and mortality as critical factors influencing aquaculture efficiency.</p>

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Investigation of influential parameters in rainbow trout aquaculture based on robust mass production planning

  • 期刊论文

  • 发表日期：

    2025年1月21日

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  • Zahra Sadaghiani Farimani,
  • Hossein Karimi,
  • Mohsen Ziaee

摘要

This paper presents a new model of production planning in rainbow trout aquaculture that aims at improving resource usage and enhancing decision-making accuracy in an effort to reduce costs and provide methods for application when dealing with uncertainty. The model caters for such operational issues as right juvenile fish purchases, fish growth rates, and the right time to harvest the fishes given capacities and mortality rate. Using a case study in Iran, both deterministic and uncertain conditions were employed in the implementation of the model, to gain a better understanding of how the production can be optimized in order to have the least cost and the highest profit rate. The paper showed the application potential of the model for fish farm managers by providing strategic insights and tools for cost minimization and risk management in an uncertain environment. The study emphasizes optimizing fish growth rates, mortality, and harvesting within fishpond capacity and market demand constraints. The findings revealed that incorporating uncertainty led to a cost increase of 20%, demonstrating the model’s resilience and applicability. Sensitivity analyses highlighted demand, growth, and mortality as critical factors influencing aquaculture efficiency.