<p>Recycling Scheme Optimization (RSO) is a critical step in improving the efficiency of resource recovery. However, current recycling scheme designs rarely take eco-efficiency as an evaluation objective, resulting in unnecessary resource waste and reduced energy conservation and emission reduction performance. To address this issue, this paper proposes an eco-efficiency-oriented optimization method for elemental recycling schemes of electronic waste. By analyzing the economic, environmental, and resource value characteristics of recyclable units and elements in electronic waste, the entropy weight method is employed to determine the scheme parameters. Furthermore, a mapping model is constructed between recycling process parameters and eco-efficiency, and a genetic algorithm is used to identify the optimal scheme. A case study on mobile phone resource recovery is conducted to validate the proposed method. The results show that the optimized scheme improves eco-efficiency by 29.74% compared to the original scheme, with economic benefits increasing by 28.96% and carbon benefits by 15%, along with various degrees of improvement in other environmental indicators. These findings demonstrate that the proposed method can effectively enhance the eco-efficiency and resource utilization of electronic waste recycling, providing valuable insights for global sustainable development.</p>