1,646 research outputs found
A novel hybrid multi-objective metamodel-based evolutionary optimization algorithm
Optimization via Simulation (OvS) is an useful optimization tool to find a solution to an optimization problem that is difficult to model analytically. OvS consists in evaluating potential solutions through simulation executions; however, its high computational cost is a factor that can make its implementation infeasible. This issue also occurs in multi-objective problems, which tend to be expensive to solve. In this work, we present a new hybrid multi-objective OvS algorithm, which uses Kriging-type metamodels to estimate the simulations results and a multi-objective evolutionary algorithm to manage the optimization process. Our proposal succeeds in reducing the computational cost significantly without affecting the quality of the results obtained. The evolutionary part of the hybrid algorithm is based on the popular NSGA-II. The hybrid method is compared to the canonical NSGA-II and other hybrid approaches, showing a good performance not only in the quality of the solutions but also as computational cost saving.Fil: Baquela, Enrique Gabriel. Universidad Tecnológica Nacional. Facultad Regional San Nicolás; ArgentinaFil: Olivera, Ana Carolina. Universidad Nacional de Cuyo. Instituto para las Tecnologías de la Informacion y las Comunicaciones; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin
RPSGAe - Reduced Pareto Set Genetic Algorithm : application to polymer extrusion
Publicado na serie "Lecture notes in economics and mathematical systems" ; 535In this paper a Multiobjective Optimization Genetic Algorithm,
denoted as Reduced Pareto Set Genetic Algorithm with Elitism
(RPSGAe), is presented and its performance is assessed. The algorithm is
compared with other Evolutionary Multi-Objective Algorithms - EMOAs
(SPEA2, PAES and NSGA-II) using problems from the literature and
statistical comparison techniques. The results obtained showed that the
RPSGAe algorithm has good overall performance. Finally, the RPSGAe
algorithm was applied to the optimization of the polymer extrusion process.
The aim is to implement an automatic optimization scheme capable
of defining the values of important process parameters, such as operating
conditions and screw geometry, yielding the best performance in terms of
prescribed attributes. The results obtained for specific case studies have
physical meaning and correspond to a successful process optimization
Cosmic Swarms: A search for Supermassive Black Holes in the LISA data stream with a Hybrid Evolutionary Algorithm
We describe a hybrid evolutionary algorithm that can simultaneously search
for multiple supermassive black hole binary (SMBHB) inspirals in LISA data. The
algorithm mixes evolutionary computation, Metropolis-Hastings methods and
Nested Sampling. The inspiral of SMBHBs presents an interesting problem for
gravitational wave data analysis since, due to the LISA response function, the
sources have a bi-modal sky solution. We show here that it is possible not only
to detect multiple SMBHBs in the data stream, but also to investigate
simultaneously all the various modes of the global solution. In all cases, the
algorithm returns parameter determinations within (as estimated from
the Fisher Matrix) of the true answer, for both the actual and antipodal sky
solutions.Comment: submitted to Classical & Quantum Gravity. 19 pages, 4 figure
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