Development of an Inexact Regional Aquaculture System Planning Model to Provide Corresponding Optimal Sustainable Resource Allocation Schemes

The Guidelines for Sustainable Aquaculture (GSAs) emphasize that formulating proper regional development plans is essential for achieving sustainable growth in aquaculture. Conventional research has limitations in allocating resources from a regional scale, subject to various constraints relating to the social, economic, environmental, and other domains. To fill this research gap, this study proposes an inexact regional aquaculture system planning model (IRAM) to optimally allocate resources including energy, water, area, media, and labor among various aquaculture species across multiple aquafarms under uncertainty. The model is applied to Fujian Province, China, over a 15-year planning horizon (2026–2040, three 5-year periods). As model-based scenario insights derived under specific assumptions, the main findings are as follows: (i) the system cost would increase by [18.75, 20.00]%, while the product output would greatly rise by [41.57, 47.54]% from period 1 to period 3; (ii) renewable energy (wind and solar) would supply [60.32, 81.05]% of the total electricity by period 3; (iii) shallow-sea culture ([48.6, 50.2]%) and pond culture ([17.6, 18.8]%) would receive the highest media allocation via internet platforms, supporting community communication; and (iv) pollutant and carbon emissions would decline due to the adoption of low-carbon feed and renewable energy penetration. The findings are scenario-dependent, and their practical applicability relies on the sensitivity analysis and model code/data availability discussed in the main text. One limitation lies in its inadequate ability to handle stochastic and fuzzy information commonly encountered in real-world planning problems.

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Publication Details

Journal
Sustainability
Published
2026-08-26
DOI
https://doi.org/10.3390/su18178761
Primary Topic
Marine Bivalve and Aquaculture Studies
Type
article
Field-Weighted Citation Impact
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article

Development of an Inexact Regional Aquaculture System Planning Model to Provide Corresponding Optimal Sustainable Resource Allocation Schemes

Xiao Li, Huabai Liu, Jing Liu, Jiawei Li et al.
Sustainability
Marine Bivalve and Aquaculture Studies
article

Development of an Inexact Regional Aquaculture System Planning Model to Provide Corresponding Optimal Sustainable Resource Allocation Schemes

Xiao Li, Huabai Liu, Jing Liu, Jiawei Li, Chen Cao
article en

Abstract

The Guidelines for Sustainable Aquaculture (GSAs) emphasize that formulating proper regional development plans is essential for achieving sustainable growth in aquaculture. Conventional research has limitations in allocating resources from a regional scale, subject to various constraints relating to the social, economic, environmental, and other domains. To fill this research gap, this study proposes an inexact regional aquaculture system planning model (IRAM) to optimally allocate resources including energy, water, area, media, and labor among various aquaculture species across multiple aquafarms under uncertainty. The model is applied to Fujian Province, China, over a 15-year planning horizon (2026–2040, three 5-year periods). As model-based scenario insights derived under specific assumptions, the main findings are as follows: (i) the system cost would increase by [18.75, 20.00]%, while the product output would greatly rise by [41.57, 47.54]% from period 1 to period 3; (ii) renewable energy (wind and solar) would supply [60.32, 81.05]% of the total electricity by period 3; (iii) shallow-sea culture ([48.6, 50.2]%) and pond culture ([17.6, 18.8]%) would receive the highest media allocation via internet platforms, supporting community communication; and (iv) pollutant and carbon emissions would decline due to the adoption of low-carbon feed and renewable energy penetration. The findings are scenario-dependent, and their practical applicability relies on the sensitivity analysis and model code/data availability discussed in the main text. One limitation lies in its inadequate ability to handle stochastic and fuzzy information commonly encountered in real-world planning problems.

SustainabilityVol. 18(17)
Xiamen University (CN), Xiamen University of Technology (CN)
Responsible consumption and production
Openalex Percentile: Top 13%
Marine Bivalve and Aquaculture Studies
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