Improved Tabu Search Method in Solving Overbooking Appointment Scheduling with No-shows Patient

Abstract

No-shows patient refer to instances where individuals either do not attend their scheduled appointments or cancel at the last minute, resulting in a missed opportunity for the health facility to utilize that time slot. This can lead to both time and financial losses for the facility, disrupting patient care. By having an efficient appointment schedule, these disruption can be overcome by minimizing resource idle time, resource overtime and patient waiting time. This research aims to enhances appointment scheduling by addressing overbooking through a heuristic approach, further refined by the tabu search method. The impact of scheduling multiple patients in the same time slot is examined to determine the optimal number of patients per slot for cost optimization. This problem is addressed using the C programming language. The findings indicate that the tabu search method slightly outperforms the heuristic approach, especially when dealing with larger patient datasets. Other than that, it is proven that the tabu search method functions effectively by having a long-term memory as it executes the programmer faster than previous methods such as genetic algorithm and simulated annealing. Besides, tabu search method is capable in improving the maximum number of patients that can be effectively assigned to the same time slot.