Applying Mixed Integer Linear Problem In Solving Covid-19 Vaccination Appointment Scheduling Problem: A Case Study In Ho Chi Minh City

Abstract

COVID-19 has had a significant impact on the world economy. The COVID-19 vaccine is widely recognized as the most promising method of combating the epidemic and assisting in the return to normalcy. By establishing appointment platforms, many countries have permitted some types of vaccines for vaccinations. Vaccination presents a significant problem to those in charge of arranging a big number of appointments. This thesis studies a vaccination site selection, appointment acceptance, appointment assignment, and scheduling problem for vaccination in response to COVID-19. An optimal solution to the problem determines the open vaccination sites, the set of accepted appointments, the assignment of accepted appointments to open vaccination sites, and the vaccination sequence at each site. The objective is to simultaneously minimize 1) the fixed cost for operating vaccination sites; 2) the traveling distance of vaccine recipients; 3) the appointment rejection cost; and 4) the vaccination tardiness cost. The problem was formulated as a mixed-integer linear program (MILP) solved by CPLEX with cost constraints such as the cost of opening the vaccination point, the non-moving cost, the rejection cost and the late cost. In addition, we have constraints with the operating time of the opening and closing points. The results showed that with a network of 22 vaccination points it was possible to process up to 4000 appointments per day and the time for each schedule was about 30 minutes. This is a perfectly feasible and subservient result to reality.