A metaheuristic to support the distribution of COVID-19 vaccines

Abstract

Paper aims:The aim is to develop a vaccine distribution routing model (VDRM) in order to support governments to mitigate the pandemic caused by COVID-19. Originality:As far as we know, no metaheuristics has been developed for vaccine distribution, and specifically, to support the Brazilian government.Research method: A metaheuristic is developed based on the combination and adaptation of GRASP (Greedy Randomized Adaptive Search Procedure) with VND (Variable Neighborhood Descent), considering different refinement operators. Finally, as a way of validating the model, a numerical application in the state of Pernambuco (Brazil) was performed.Main findings: Metaheuristic proved to be effective for developing adequate planning for the allocation of ampoules with vaccines to combat COVID-19. Effective analysis was obtained in the evaluation of the proposed algorithm, both in terms of computational effort and the quality of the final solution. An efficiency of approximately 75% was obtained in relation to the current distribution procedure adopted by the state of Pernambuco. Implications for theory and practice:To mitigate disease, adequate logistics for transporting and distributing vaccines is essential, especially in emergency situations to face pandemic crises. Thus, the developed metaheuristic can support governments and companies in any situation demanded, making the decision of how the distribution of the ampoules will be more agile.

Vehicle Routing Optimization for Pandemic Containment: A Systematic Review on Applications and Solution Approaches

“…In contrast, Jiang et al [70] suggested the minimization of average arrival time, taking into account all routes. If the travel time for a route is not directly available, the travel distance might be used to estimate it; therefore, another practical approach to measuring the response time is the minimization of the total travel distance [73,83,97,100].…”

“…In addition, the time at which vaccines are delivered to each area has an effect on the regional demand, since any delay in obtaining a vaccine may result in an increase in infected people. In this regard, researchers have developed a route optimization tool [95,97] for efficiently distributing vaccines, as well as simulation tools [80] for estimating the amount of vaccines required based on the priority in each region.…”

“…Martinez-Reyes (2021) [99] Martins (2021) [107] Mehlawat (2021) [85] Ozkan (2021) [83] Petroianu (2021) [95] Rodrigues (2021) [97] Wu (2021) [ With respect to model characteristics, most work considered pharmaceutical transportation as a VRPTW with a focus on the time limit of vehicles. Time restrictions on customer location and depot were still lacking in the reviewed papers within this area.…”

“…Regarding the solution approach, most work used metaheuristic and heuristic approaches to accelerate the generation of a routing plan. Population-based algorithms [52,71,79,85,94,97,103] prevailed in the pharmaceutical transportation problem; heuristics are often used to cluster customers [52,93] or develop a feasible solution first [96,104], followed by the implementation of exact solution procedures [68,80,83] or learning-based algorithms [104] to enhance the solution. Furthermore, the ML technique is utilized in [116] with a focus on the determination of potential depots.…”