A discrete particle swarm optimization method for assignment of supermarket resources to urban residential communities under the situation of epidemic control

Differential evolution and particle swarm optimization against COVID-19

“…In the majority of DE applications against COVID-19 authors do not clarify the population size used. The impact of the population size on the results is almost never analyzed, with the exception of bi-objective study by Zou et al ( 2020 ) aimed at PSO-DE hybrid, for which 30 individuals turned out the best choice. When population size is given (see Table 1 ), it almost always ranges from 15 to 50 individuals.…”

“…However, the fixed inertia weight set to 0.9 (Bhonde et al 2020 ; Dutra et al 2020 ), 0.7 (Fister et al 2020a ), or to the value of 0.729 (Kergassner et al 2020 ) suggested in Clerc and Kennedy ( 2002 ) (which should be accompanied by the specific setting of acceleration coefficients), and an unexpected very small value of 0.2 (Issa and Abd Elaziz 2020 ) are also used. In PSO-DE bi-objective hybrid (Zou et al 2020 ) extremely low values of acceleration coefficients and inertia weight were used, but this may be due to the hybridization interactions with DE counterpart. Hence, as in the case of DE, one may conclude that in the majority of studies that use PSO against COVID-19 in which inertia weight and acceleration coefficients are specified, their choices follow suggestions from the PSO literature.…”

“… ? Comparisons for 14 hospitals are shown; results for transformed problems are much better; depending on the hospital, the best performance is obtained by MOPSO, DEMOwSA or MOEA/D Discussed algorithms are used to find solutions of 2-objective problems; these are then divided into 1-objective low-dimensional sub-problems that are solved by Tabu search Goods management during COVID-19 pandemic Zou et al ( 2020 ) Goods assignment for supermarkets to address residents needs during pandemics 1000 supermarkets and 6758 communities 2 1. PSO-DE (Zou et al, 2020 ) 2.…”

“…Wu et al ( 2020 ) found that among 5 competitors, the algebraic DE variant (Santucci et al 2016 ) is the best method for mask-production real-time scheduling task. Discrete hybridization of PSO and DE has also been compared against three other metaheuristics for goods assignment maximization during COVID-19 pandemic and the risk of infection minimization (Zou et al 2020 ); the hybrid approach was praised, but it seems to perform better for the infection minimization criterion than for goods assignment problem.…”

Supply chain design to tackle coronavirus pandemic crisis by tourism management

“…Also, Saadat et al [21] examined the extent to which environmental pollution was reduced during the COVID-19. Moreover,​ Kargar et al [22] investigated the waste management of medical centers, Vaka et al [23] that compared the factors affecting renewable energy in Malaysia in the COVID-19 pandemic in Asian countries, and Zou et al [24] developed a distribution system for supermarkets in pandemic situation.…”