DentDES: code, synthetic data and results for a factorial discrete-event evaluation of appointment spacing and readiness-aware dispatch in dental clinics

<p dir="ltr">Code, synthetic input data, archived results and diagnostics for the paper "DentDES: A Factorial Discrete-Event Evaluation of Appointment Spacing and Readiness-Aware Dispatch in Dental Clinics" (ISMSIT 2026).</p><p dir="ltr">The Python and SimPy model compares two appointment-spacing rules and two dispatch rules (strict first-come-first-served and readiness-aware dispatch with a bypass bound of two) across four demand levels and three instrument-kit capacities.

Each condition has 50 paired replication blocks of 30 clinic days (72,000 clinic-day runs). The archive also contains 36,000 exploratory diagnostic runs, validation scripts and recorded checks.</p><p dir="ltr">All inputs are synthetic and no patient data were used. Results describe the model and are not estimates of effects in a real clinic.