Genetic algorithm and particle swarm optimization combined with Powell method

Bento, David; Pinho, Diana; Pereira, Ana I.; Lima, Rui

doi:10.1063/1.4825557

Cited by 7 publications

(2 citation statements)

References 6 publications

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“…Individuals with less value have a high probability of being selected whereas the new generation of individuals may have a minor objective value than the previous generation. The evolution process is repeated until the stopping criterion is satisfied (Bento et al, 2013(Bento et al, , 2015Catlin et al, 2011;Kumar et al, 2010). In this work it was implemented the genetic algorithm proposed by Bento et al (2013Bento et al ( , 2015 using Matlab software.…”

Section: Global Optimisation Method: Genetic Algorithmmentioning

confidence: 99%

Cell-free layer analysis in a polydimethysiloxane microchannel: a global approach

Pinto

Faustino

Pinho

et al. 2016

IJMEI

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The cell-free layer (CFL) is a hemodynamic phenomenon that has an important contribution to the rheological properties of blood flowing in microvessels. The present work aims to find the closest function describing RBCs flowing around the cell depleted layer in a polydimethysiloxane (PDMS) microchannel with a diverging and a converging bifurcation. The flow behaviour of the CFL was investigated by using a high-speed video microscopy system where special attention was devoted to its behaviour before the bifurcation and after the confluence of the microchannel. The numerical data was first obtained by using a manual tracking plugin and then analysed using the genetic algorithm approach. The results show that for the majority of the cases the function that more closely resembles the CFL boundary is the sum of trigonometric functions.

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Section: Global Optimisation Method: Genetic Algorithmmentioning

confidence: 99%

Cell-free layer analysis in a polydimethysiloxane microchannel: a global approach

Pinto

Faustino

Pinho

et al. 2016

IJMEI

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“…The iterative procedure terminates after a maximum number of iterations (number of generations) or after a maximum number of function evaluations [1,3]. The information referred to above concerns centralized decisions, which will allow to calculate the optimized schedule that is passed to the on-line module.…”

Section: End Whilementioning

confidence: 99%

Scheduling of Home Health Care Services Based on Multi-agent Systems

Alves

Pereira

Barbosa

et al. 2018

Highlights of Practical Applications of Agents, Multi-Agent Systems, and Complexity: The PAAMS Collection

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Home Health Care (HHC) services are growing worldwide and, usually, the home care visits are manually planned, being a time and effort consuming task that leads to a non optimized solution. The use of some optimization techniques can significantly improve the quality of the scheduling solutions, but lacks the achievement of solutions that face the fast reaction to condition changes. In such stochastic and very volatile environments, the fast rescheduling is crucial to maintain the system in operation. Taking advantage of the inherent distributed and intelligent characteristics of Multi-agent Systems (MAS), this paper introduces a methodology that combines the optimization features provided by centralized scheduling algorithms, e.g. genetic algorithms, with the responsiveness features provided by MAS solutions. The proposed approach was codified in Matlab and NetLogo and applied to a realworld HHC case study. The experimental results showed a significant improvement in the quality of scheduling solutions, as well as in the responsiveness to achieve those solutions.

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