IMPLEMENTATION OF METAHEURISTIC METHODS IN STRATEGY FOR MAPPING ALLOCATION OF COVID-19 VACCINE IN INDONESIA

• Main Author: Dwikifirdaus, Rizvan
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/55133
• Institution: Institut Teknologi Bandung

COVID-19 is an infectious disease caused by the SARS-CoV-2 virus. COVID-19 was later characterized as a pandemic and the disease also spreading in Indonesia. One of the strategies to reduce the rate of transmission of the SARS-CoV-2 virus in a population is by vaccination. The limited amount of vaccines and the differences in the epidemiological characteristics of COVID-19 for various age groups have resulted in the need for a mapping strategy for the allocation of COVID-19 vaccines, which considered as the constrained optimization problems. In this final project, several metaheuristic methods were used, which are Genetic Algorithm (GA), Differential Evolution (DE), and Particle Swarm Optimization (PSO) to determine used the optimal COVID-19 vaccine allocation strategy with various vaccine availability scenarios. In this final project, the penalty method is also used to modify the algorithm so that it can work to solve the constrained optimization problem in a more general way. In the case discussed in this final project, the PSO method gives the best vaccination strategy with the minimum number of losses from COVID-19. Various vaccine distribution priorities are also presented for several scenarios of vaccine availability in Indonesia.