Multiobjective Genetic Algorithm applied to dengue control

Florentino, Helenice de Oliveira; Cantane, Daniela Renata; Santos, Fernando Luiz Pio dos; Bannwart, Bettina Fiorini

doi:10.1016/j.mbs.2014.08.013

Cited by 23 publications

(13 citation statements)

References 7 publications

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“…The inertia weight ω gradually drops to 0.4 from the initial value 1.0, which is to control the impact of history velocity on the current velocity. r1 f and r1 f are both random values in the range [0,1], and the population size is set to 50 and 100, while the program is to run 200 generations. The Pareto archive is limited to 100.…”

Section: Simulation Results and Analysismentioning

confidence: 99%

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An effective solution to finding global best guides in particle swarm for typical MOPs

Liu¹

2017

Proceedings of the 2016 International Forum on Mechanical, Control and Automation (IFMCA 2016)

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Abstract. It is of critical importance for convergence and diversity of final solutions that finding out a feasible global best guide for each particle of the current swarm in multi-objective particle swarm optimization (MOPSO). An improved approach for determining the best local guide in MOPSO is proposed, where the Pareto archive with size limit is used to store the non-dominated solutions. While selecting the local best particle, a random number is used to judge whether the crowding distance is taken into account or not. A new solution is referred to overcome the problem that it is much harder to generate a new particle dominating the original one in MOPs than in single-objective optimal problems. In addition, to improve the efficiency of search and avoid precocity, the inertial weight changes in the iteration process. The proposed approach is applied to some typical testing functions, and the experimental results of Pareto fronts for these functions are satisfied.

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Section: Simulation Results and Analysismentioning

confidence: 99%

“…One of the major problems existing today in the area of science research and industrial practice is multi-objective optimization problem (MOP) [1,2]. The most important characteristic of MOP, which is different with single objective problem, is the final solutions.…”

Section: Introductionmentioning

confidence: 99%

An effective solution to finding global best guides in particle swarm for typical MOPs

Liu¹

2017

Proceedings of the 2016 International Forum on Mechanical, Control and Automation (IFMCA 2016)

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“…Previous works 15,36 have proposed obtaining different optimal policies for IVM of mosquito-borne disease through a bi-objective optimization, considering as one objective the minimization of the control costs while the other objective function aims to maximize the population of sterile males. There are some underlined ideas supporting that choice.…”

Section: The Multiobjective Optimization Problemmentioning

confidence: 99%

A receding horizon control approach for integrated vector management of Aedes aegypti using chemical and biological control: A mono and a multiobjective approach

Jesus

Wanner

Cardoso

2019

Math Methods in App Sciences

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This paper addresses an integrated vector management (IVM) approach for combating Aedes aegypti, the transmission vector of dengue, zika, and chikungunya diseases, some of the most important viral epidemics worldwide. In order to tackle this problem, a receding horizon control (RHC) strategy is adopted, considering a mono‐objective and a multiobjective version of the optimal control model of combating the mosquito using chemical and biological control. RHC is essentially a suboptimal scheme of classical optimal control strategies considering discrete‐time approximations. The integrated vector control actions used in this work consist in applying insecticides and inserting sterile males produced by irradiation in the population of mosquitoes. The cost function is defined in terms of social and economic costs, in order to quantify the effectiveness of the proposed epidemiological control throughout a time window of 4 months. Numerical simulations show that the obtained results are better than those from the optimal control strategies found in literature. Furthermore, through the application of the multiobjetive approach, varying the scenarios in the mono‐objective formulation is no longer necessary and a set of optimal strategies can be obtained at once. Finally, in order to help health authorities in the choice of the best solution of the Pareto‐optimal set to be implemented in practice, a cost‐effectiveness analysis is performed and a strategy representing the most cost‐effective control policy is obtained.

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“…The control variables are embedded in the models of epidemics. Then, the optimal settings of these variables are obtained using optimal algorithms, in order to suppress the spread of dengue fever [20][21][22]. In conclusion, according to the best of the authors' knowledge, a model for exploring the infectious sites of dengue fever has not yet been studied.…”

Section: Introductionmentioning

confidence: 99%

Latent Infectious Capacities of Dengue Fever: Mathematical Modeling and Eco-Friendly Prevention Strategy

Hong

2020

Symmetry

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The main aim of this article is to propose a method for exploring the latent values about the capacities of spreading dengue for each potential site. First, a mathematical model connecting the observable public data and the capacities of spreading dengue is provided based on the split feasibility problem (SFP). Then, a proper iterative scheme for the SFP is presented to approach the values of infectious capacities (ICs) of potential sites-the capacities of spreading. The performance of our proposed method is demonstrated using public data from Kaohsiung City for 2014 and 2015. The results presented in this paper show that our proposed method is reliable and the sites with a high capacity of spreading are only a small portion of thousands of all potential sites and could be an alternative strategy for preventing the outbreak of dengue fever whilst also avoiding the damage of ecosystems caused by chemical insecticides.

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Multiobjective Genetic Algorithm applied to dengue control

Cited by 23 publications

References 7 publications

An effective solution to finding global best guides in particle swarm for typical MOPs

An effective solution to finding global best guides in particle swarm for typical MOPs

A receding horizon control approach for integrated vector management of Aedes aegypti using chemical and biological control: A mono and a multiobjective approach

Latent Infectious Capacities of Dengue Fever: Mathematical Modeling and Eco-Friendly Prevention Strategy

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