Mathematical modeling of the spread of the coronavirus disease 2019 (COVID-19) taking into account the undetected infections. The case of China
In this paper we develop a mathematical model for the spread of the coronavirus disease
2019 (COVID-19). It is a new θ-SEIHRD model (not a SIR, SEIR or other general purpose …
2019 (COVID-19). It is a new θ-SEIHRD model (not a SIR, SEIR or other general purpose …
A survey of multiobjective evolutionary algorithms based on decomposition
Decomposition is a well-known strategy in traditional multiobjective optimization. However,
the decomposition strategy was not widely employed in evolutionary multiobjective …
the decomposition strategy was not widely employed in evolutionary multiobjective …
A review and evaluation of multi and many-objective optimization: Methods and algorithms
F Karami, AB Dariane - Global Journal of Ecology, 2022 - agriscigroup.us
Most optimization problems naturally have several objectives, usually in conflict with each
other. The problems with two or three objective functions are referred to as Multi-Objective …
other. The problems with two or three objective functions are referred to as Multi-Objective …
A novel whale optimization algorithm integrated with Nelder–Mead simplex for multi-objective optimization problems
M Abdel-Basset, R Mohamed, S Mirjalili - Knowledge-Based Systems, 2021 - Elsevier
Recently, several meta-heuristics and evolutionary algorithms have been proposed for
tackling optimization problems. Such methods tend to suffer from degraded performance …
tackling optimization problems. Such methods tend to suffer from degraded performance …
An overview of weighted and unconstrained scalarizing functions
M Pescador-Rojas, R Hernández Gómez… - … Conference, EMO 2017 …, 2017 - Springer
Scalarizing functions play a crucial role in multi-objective evolutionary algorithms (MOEAs)
based on decomposition and the R2 indicator, since they guide the population towards …
based on decomposition and the R2 indicator, since they guide the population towards …
A survey of normalization methods in multiobjective evolutionary algorithms
A real-world multiobjective optimization problem (MOP) usually has differently scaled
objectives. Objective space normalization has been widely used in multiobjective …
objectives. Objective space normalization has been widely used in multiobjective …
Evolutionary multi-objective optimization algorithms for fuzzy portfolio selection
In this paper, we consider a recently proposed model for portfolio selection, called Mean-
Downside Risk-Skewness (MDRS) model. This modelling approach takes into account both …
Downside Risk-Skewness (MDRS) model. This modelling approach takes into account both …
Decomposition-based-sorting and angle-based-selection for evolutionary multiobjective and many-objective optimization
Multiobjective evolutionary algorithm based on decomposition (MOEA/D) decomposes a
multiobjective optimization problem (MOP) into a number of scalar optimization subproblems …
multiobjective optimization problem (MOP) into a number of scalar optimization subproblems …
[PDF][PDF] Mathematical modeling of the spread of the coronavirus disease 2019 (COVID-19) considering its particular characteristics. The case of China
B Ivorra, MR Ferrández… - … Sci. Numer. Simul, 2020 - enastava.matf.bg.ac.rs
In this paper we develop a mathematical model for the spread of the coronavirus disease
2019 (COVID-19). We use a compartmental model (but not a SIR, SEIR or other general …
2019 (COVID-19). We use a compartmental model (but not a SIR, SEIR or other general …
A simple but complex enough θ-SIR type model to be used with COVID-19 real data. Application to the case of Italy
Since the start of the COVID-19 pandemic in China many models have appeared in the
literature, trying to simulate its dynamics. Focusing on modeling the biological and …
literature, trying to simulate its dynamics. Focusing on modeling the biological and …