Shicheng Zhou
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Shicheng Zhou has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Dong Wang
School of Information and Electrical Engineering, Hebei University of Engineering, Handan 056038, China
1 shared publication - Xin Liu
School of Information and Electrical Engineering, Hebei University of Engineering, Handan 056038, China
1 shared publication - Yongqiang Ma
School of Information and Electrical Engineering, Hebei University of Engineering, Handan 056038, China
1 shared publication - Zhen Liu
School of Information and Electrical Engineering, Hebei University of Engineering, Handan 056038, China
1 shared publication
Latest Publications
- Open Access
Equity-Oriented Multi-Objective Optimization Allocation Strategies for Urban Water Resources
Urban water usage spans diverse sectors, requiring effective management strategies to address increasing demand, limited supplies, and sector-specific needs. In this study, a multi-objective urban water resource allocation model is proposed to balance economic, ecological, and social benefits, focusing on social fairness. The model considers water availability, demand diversity, and environmental factors for optimized resource allocation. An improved zebra optimization algorithm-based multi-objective evolutionary algorithm (ZOA-MOEA/D) is developed, integrating zebra optimization with a decomposition-based approach to overcome the traditional methods’ limitations, improving solution diversity and convergence. ZOA-MOEA/D consistently outperforms the NSGA-II, MOPSO, and MOEA/D algorithms in solution distribution, convergence, quality, and diversity across multiple test scenarios. By applying the model to Ningbo, China, key trade-offs between economic growth, social fairness, living standards, and ecological protection are revealed. These findings provide useful insights into urban water resource management, offering a flexible framework for balancing multiple objectives and supporting sustainable development. Despite some limitations, the approach can contribute to the ongoing development of urban water resources.
Open AccessEquity-Oriented Multi-Objective Optimization Allocation Strategies for Urban Water Resources
Urban water usage spans diverse sectors, requiring effective management strategies to address increasing demand, limited supplies, and sector-specific needs. In this study, a multi-objective urban water resource allocation model is proposed to balance economic, ecological, and social benefits, focusing on social fairness. The model considers water availability, demand diversity, and environmental factors for optimized resource allocation. An improved zebra optimization algorithm-based multi-objective evolutionary algorithm (ZOA-MOEA/D) is developed, integrating zebra optimization with a decomposition-based approach to overcome the traditional methods’ limitations, improving solution diversity and convergence. ZOA-MOEA/D consistently outperforms the NSGA-II, MOPSO, and MOEA/D algorithms in solution distribution, convergence, quality, and diversity across multiple test scenarios. By applying the model to Ningbo, China, key trade-offs between economic growth, social fairness, living standards, and ecological protection are revealed. These findings provide useful insights into urban water resource management, offering a flexible framework for balancing multiple objectives and supporting sustainable development. Despite some limitations, the approach can contribute to the ongoing development of urban water resources.