The main objective of this paper is to solve the optimization problem that is associated with the classification of DNA samples in PCR plates for Sanger sequencing. To achieve this goal, we design an integer linear programming model. Given that the real instances involve the classification of thousands of samples and the linear model can only be solved for small instances, the paper includes a heuristic to cope with bigger problems. The heuristic algorithm is based on the simulated annealing technique. This algorithm obtains satisfactory solutions to the problem in a short amount of time. It has been tested with real data and yields improved results compared to some commercial software typically used in (clinical) laboratories. Moreover, the algorithm has already been implemented in the laboratory and is being successfully used.

翻译：本文的主要目标是解决桑格测序中PCR板内DNA样本分类相关的优化问题。为实现这一目标，我们设计了一个整数线性规划模型。鉴于实际案例涉及数千个样本的分类，且该线性模型仅能求解小规模问题，本文提出了一种启发式算法以应对更大规模的问题。该启发式算法基于模拟退火技术，能够在短时间内获得问题的满意解。该算法已使用真实数据进行测试，与（临床）实验室常用的一些商业软件相比，其得出的结果更为优越。此外，该算法已在实验室中成功实施并投入使用。