Shipment Forecasting for Yellowtail Aquaculture Using Monte Carlo Simulation: A Scenario Analysis on the Utilization of Hatchery-Produced Juveniles

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Authors: Yûki Kimura, Tomomi Nonaka
Cited by: 0
References: 3

Abstract

In Japan’s key yellowtail ( buri ) aquaculture industry, the increasing exports are contrasted with the production instability caused by declining producers and a reliance on wild juveniles with long, unpredictable lead times. This study addresses these challenges by proposing a production management approach that utilizes hatchery-produced juveniles with controllable, twice-yearly spawning schedules (spring and autumn) to improve the efficiency and predictability. A Monte Carlo simulation using probability distributions determined by the Anderson–Darling test was employed to analyze the shipment patterns and revenue under three pricing scenarios: high-seasonal, moderate, and size-differentiated. The results demonstrate that an increase in the number of spawning seasons distributes shipments more uniformly. This results in a stable year-round supply. The approach can significantly increase the annual revenue, particularly in the high-seasonal price scenario. Conversely, although the differentiated pricing model marginally reduces the total revenue, it significantly mitigates seasonal sales fluctuations. Thus, it provides enhanced stability for producers. To conclude, this study shows that utilizing hatchery-produced juveniles enhances the economic resilience and operational sustainability. This shift toward a more controlled and efficient system aligns with the core sustainability principles. The methodology also provides an adaptable model for other aquaculture sectors. Future work should incorporate the market demand and environmental variables to develop more comprehensive decision-making tools.

Fields of Study & Subjects

Marine Bivalve and Aquaculture Studies Marine and fisheries research Aquaculture Nutrition and Growth

Publication details

Journal / source
International Journal of Automation Technology
Volume
20
Issue
1
Pages
38–46
Publication date
4 January 2026
Language
EN