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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
Published on: December 9, 2012
Sustainable intelligent product development through systemic optimization of value, cost, and environmental
Zishun Su1, Xinyan Jiang2, Qiaoling Zou3
1School of Digital Technology and Innovation Design, Jiangnan University, Wuxi, 214401, China.
None:
Integrating sustainability into intelligent product development presents significant challenges in balancing functionality, cost, and environmental/social responsibility, particularly during conceptual design where stakeholder conflicts emerge. We develop a tripartite stochastic evolutionary game model incorporating random disturbances to analyze interactions among contractors, clients, and users, employing sensitivity analysis to identify key parameters for sustainable optimization. The system achieves evolutionary stability despite uncertainties. Analysis reveals that optimizing subsidies, revenue-sharing, and feedback mechanisms effectively steers evolution toward improved environmental performance. A case study demonstrates enhanced adaptability and long-term sustainable competitiveness. Strategic incentive mechanisms enable the integration of cost-efficiency, innovation, and sustainability objectives, resolving stakeholder conflicts and advancing environmentally conscious value creation in intelligent product development.
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