The study explores the optimization of evolutionary solver parameters for minimizing total tardiness in single machine scheduling, an NP-hard problem with zero ready times included. It investigates various parameter combinations, including population sizes, mutation rates, and a constant convergence rate, both above and below default values. The aim is to enhance the solver's effectiveness in addressing this complex challenge. The findings contribute to improving scheduling efficiency in manufacturing and operations management contexts.

翻译：本研究探索了进化求解器参数的优化问题，以最小化单机调度中的总拖期时间——这是一个包含零就绪时间的NP难问题。研究考察了多种参数组合，包括种群规模、变异率以及恒定收敛率，这些参数均处于默认值的上下范围。其目标在于提升求解器应对这一复杂挑战的有效性。研究结果有助于提高制造业及运营管理中的调度效率。