Integrated consultation and chemotherapy scheduling with stochastic treatment times

This paper studies the integrated scheduling of consultation and treatment appointments for chemotherapy patients, while taking into account the stochastic duration of injection. Patients may require one or both types of consultation and treatment appointments. The objective is to minimize the clinic's overtime and the waiting time of patients in the clinic. To formulate the problem, we develop two two-stage stochastic programming models. We also propose a sample average approximation algorithm as the solution method. To improve the efficiency of our solution approach, we devise a specialized algorithm that quickly evaluates a given first-stage solution for a large set of scenarios, without solving the second-stage models. Several computational experiments are carried out to evaluate the performance of proposed models and algorithms.

Automated summary

This paper examines the integrated scheduling of consultation and treatment appointments for chemotherapy patients, taking into account the stochastic duration of injection. The objective is to minimize the clinic's overtime and patients' waiting time. Two-stage stochastic programming models and a sample average approximation algorithm are developed as solution methods to address the problem.