  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.
