Optimizing sustainable fishery resource allocation in China: an improved adaptive NSGA-III approach under multi-dimensional rigid constraints

Introduction Multi-dimensional fishery resource allocation presents a complex and highly nonlinear optimization challenge under the converging pressures of ecological redlines and industrial transformation. Existing allocation approaches often struggle to coordinate production, processing, and marketing under rigid ecological and capacity constraints, thereby limiting the sustainable transition of China’s fishery sector. Methods Using decade-long longitudinal data from China (2014–2023), this study develops a production–processing–marketing (PPM) synergy framework for multi-dimensional fishery resource allocation. The framework integrates rigid constraints, including strict catch limits, processing capacities, and spatial thresholds, to simultaneously optimize economic returns, production structures, and infrastructure efficiency. To solve the resulting ultra-high-dimensional and non-convex optimization problem, an Improved Adaptive NSGA-III (IA-NSGA-III) is proposed. The algorithm incorporates two key strategies: an adaptive reference point relocation mechanism to improve Pareto front coverage under non-uniform objectives, and a constraint-violation-feedback-based heuristic evolutionary operator with hierarchical selection logic to accelerate convergence in high-feasibility regions. Results The empirical results show that IA-NSGA-III outperforms standard NSGA-III and MOEA/D in both convergence and solution quality. Specifically, the proposed algorithm achieves a Hypervolume (HV) of 0.96 and a minimum Inverted Generational Distance (IGD) of 0.012. In addition, the proposed model improves synergistic resource efficiency by 15.2%–20.4% while maintaining near-perfect ecological security satisfaction ( η eco ≈99.981%, η eco ≈99.981%). The ablation analysis further reveals that neglecting midstream processing results in a 23.1% decline in social reliability, whereas digitalization significantly enhances systemic resilience. Discussion These findings indicate that the proposed PPM synergy framework and IA-NSGA-III provide an effective decision-support tool for balancing ecological protection, industrial coordination, and resource efficiency in multi-dimensional fishery systems. The study offers a robust analytical basis for promoting the sustainable transformation and resilience of China’s fishery sector under rigid ecological and industrial constraints.

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Publication Details

Journal
Frontiers in Marine Science
Published
2026-04-13
DOI
https://doi.org/10.3389/fmars.2026.1809036
Primary Topic
Marine and fisheries research
Type
article
Field-Weighted Citation Impact
0.00

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article

Optimizing sustainable fishery resource allocation in China: an improved adaptive NSGA-III approach under multi-dimensional rigid constraints

Na Liu, Ning Mao, Jinmin Huang
Frontiers in Marine Science
Marine and fisheries research
article

Optimizing sustainable fishery resource allocation in China: an improved adaptive NSGA-III approach under multi-dimensional rigid constraints

Na Liu, Ning Mao, Jinmin Huang
article en

Abstract

Introduction Multi-dimensional fishery resource allocation presents a complex and highly nonlinear optimization challenge under the converging pressures of ecological redlines and industrial transformation. Existing allocation approaches often struggle to coordinate production, processing, and marketing under rigid ecological and capacity constraints, thereby limiting the sustainable transition of China’s fishery sector. Methods Using decade-long longitudinal data from China (2014–2023), this study develops a production–processing–marketing (PPM) synergy framework for multi-dimensional fishery resource allocation. The framework integrates rigid constraints, including strict catch limits, processing capacities, and spatial thresholds, to simultaneously optimize economic returns, production structures, and infrastructure efficiency. To solve the resulting ultra-high-dimensional and non-convex optimization problem, an Improved Adaptive NSGA-III (IA-NSGA-III) is proposed. The algorithm incorporates two key strategies: an adaptive reference point relocation mechanism to improve Pareto front coverage under non-uniform objectives, and a constraint-violation-feedback-based heuristic evolutionary operator with hierarchical selection logic to accelerate convergence in high-feasibility regions. Results The empirical results show that IA-NSGA-III outperforms standard NSGA-III and MOEA/D in both convergence and solution quality. Specifically, the proposed algorithm achieves a Hypervolume (HV) of 0.96 and a minimum Inverted Generational Distance (IGD) of 0.012. In addition, the proposed model improves synergistic resource efficiency by 15.2%–20.4% while maintaining near-perfect ecological security satisfaction ( η eco ≈99.981%, η eco ≈99.981%). The ablation analysis further reveals that neglecting midstream processing results in a 23.1% decline in social reliability, whereas digitalization significantly enhances systemic resilience. Discussion These findings indicate that the proposed PPM synergy framework and IA-NSGA-III provide an effective decision-support tool for balancing ecological protection, industrial coordination, and resource efficiency in multi-dimensional fishery systems. The study offers a robust analytical basis for promoting the sustainable transformation and resilience of China’s fishery sector under rigid ecological and industrial constraints.

Frontiers in Marine ScienceVol. 13
EA Technology (GB), Nanjing Hydraulic Research Institute (CN), Chinese Academy of Fishery Sciences (CN)
East China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences
Openalex Percentile: Top 21%
Marine and fisheries research
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