在法庭科学领域，犯罪现场的混合DNA证据常包含多个个体遗传信息，其准确解析是案件侦破和司法裁决的关键。随着法医遗传学技术的发展，虽检测能力有所提升，但多供者分型解析仍存在瓶颈，传统方法难以同时精准推断嫌疑人基因型及贡献比例，无法满足复杂混合样本解析的高要求。针对上述问题，本文提出基于概率残差优化的伽马分布连续模型算法，通过构建两步概率评估架构，先基于等位基因排列组合生成候选基因型组合并计算初步贡献比例，再引入伽马分布假设构建概率密度函数，动态优化形状参数α和尺度参数β以计算残差概率权重，经迭代式极大似然估计同步优化基因型组合与贡献度参数，结合群体基因频率数据库输出最大似然值解析结果。该算法可为司法鉴定提供可量化评估的可靠工具，显著提升复杂混合样本解析准确性，增强混合DNA辅助侦查效能，对推动法庭科学技术进步、保障司法公正意义重大。

In the field of forensic science, mixed DNA evidence obtained from crime scenes often contains genetic information from multiple individuals, and its accurate interpretation is crucial for case investigation and judicial decision-making. With the advancement of forensic genetic technologies, although detection capabilities have significantly improved, there are still substantial bottlenecks in the interpretation of multi-contributor DNA profiles. Traditional methods are often unable to simultaneously and precisely infer both the genotypes of suspects and their respective contribution proportions, which makes them insufficient to meet the stringent requirements of complex mixture analysis. To address these challenges, we propose a continuous gamma distribution model algorithm based on probabilistic residual optimization in this study. By constructing a two-step probabilistic evaluation framework, the algorithm first generates candidate genotype combinations through allelic permutations and estimates preliminary contributor proportions. It then introduces the gamma distribution hypothesis to build a probability density function, dynamically optimizes the shape parameter (α) and the scale parameter (β) to calculate residual probability weights, and employs an iterative maximum likelihood estimation process to simultaneously optimize genotype combinations and contributor proportion parameters. The final results are derived by integrating population allele frequency databases to output the maximum likelihood solution. This algorithm provides a reliable and quantifiable analytical tool for forensic identification, significantly improving the accuracy of complex mixture interpretation and enhancing the practical utility of mixed DNA in criminal investigations. It holds substantial significance in advancing forensic science technologies and safeguarding judicial fairness.