Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Ricardo Landa-Becerra"'
Publikováno v:
APPLIED SOFT COMPUTING
Artículos CONICYT
CONICYT Chile
instacron:CONICYT
Artículos CONICYT
CONICYT Chile
instacron:CONICYT
This paper addresses the solution of timetabling problems using cultural algorithms. The core idea is to extract problem domain information during the evolutionary search, and then combine it with some previously proposed operators, in order to impro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0b6f7ec4969ff65676da5bfe70ce2369
https://doi.org/10.1016/j.asoc.2009.11.024
https://doi.org/10.1016/j.asoc.2009.11.024
Publikováno v:
Materials and Manufacturing Processes. 24:119-129
This article provides a short introduction to the evolutionary multiobjective optimization field. The first part of the article discusses the most representative multiobjective evolutionary algorithms that have been developed, from a historical persp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dff7070147b07ef2508a38704b9a7006
https://doi.org/10.1080/10426910802609110
https://doi.org/10.1080/10426910802609110
Publikováno v:
Engineering Optimization. 39:69-85
In this work, an approach for solving the job shop scheduling problem using a cultural algorithm is proposed. Cultural algorithms are evolutionary computation methods that extract domain knowledge during the evolutionary process. Additional to this e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0aef75d24afd269829a34d791e5a0eea
https://doi.org/10.1080/03052150600956811
https://doi.org/10.1080/03052150600956811
Publikováno v:
Computer Methods in Applied Mechanics and Engineering. 195:4303-4322
A cultural algorithm with a differential evolution population is proposed in this paper. This cultural algorithm uses different knowledge sources to influence the variation operator of the differential evolution algorithm, in order to reduce the numb
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eaf6bd6a789eee5e7b13130a3ec02ee3
https://doi.org/10.1016/j.cma.2005.09.006
https://doi.org/10.1016/j.cma.2005.09.006
Publikováno v:
IEEE Congress on Evolutionary Computation
In recent years, the development of hybrid approaches to solve multiobjective optimization problems has become an important trend in the evolutionary computation community. Despite hybrid approaches of mathematical programming techniques with multiob
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::55833c5afd5f658b82fdd29c4b13f06b
https://doi.org/10.1109/cec.2013.6557568
https://doi.org/10.1109/cec.2013.6557568
Publikováno v:
IEEE Congress on Evolutionary Computation
In recent years, the development of selection mechanisms based on performance indicators has become an important trend in algorithmic design. Hereof, the hypervolume has been the most popular choice. Multi-objective evolutionary algorithms (MOEAs) ba
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0e02fd9cd86a5a9f3bffcb15b850e39d
https://doi.org/10.1109/cec.2013.6557743
https://doi.org/10.1109/cec.2013.6557743
Publikováno v:
IEEE Congress on Evolutionary Computation
In recent years, Evolutionary Algorithms (EAs) have been widely used to solve difficult optimization problems. However, when these problems are expensive (computationally speaking), they can remain intractable even by these approaches. The EA communi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3a84b9746712c69cdd641582fc164537
https://doi.org/10.1109/cec.2013.6557875
https://doi.org/10.1109/cec.2013.6557875
Publikováno v:
Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases ISBN: 9783540774662
Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases
Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases
This chapter presents a survey of techniques used to incorporate knowledge into evolutionary algorithms, with a particular emphasis on multi-objective optimization. We focus on two main groups of techniques: those that incorporate knowledge into the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d05dc4aa72ae32c2719743902ff8a22e
https://doi.org/10.1007/978-3-540-77467-9_2
https://doi.org/10.1007/978-3-540-77467-9_2
Autor:
Ricardo Landa Becerra, Rafael Caballero, Carlos A. Coello Coello, Alfredo G. Hernández-Díaz, Julián Molina
Publikováno v:
GECCO
In this paper, we propose the combination of different optimization techniques in order to solve "hard" two- and three-objective optimization problems at a relatively low computational cost. First, we use the e-constraint method in order to obtain a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::80b2be1e9bc836a41f8a1828dec1ef60
https://doi.org/10.1145/1276958.1277113
https://doi.org/10.1145/1276958.1277113
Publikováno v:
GECCO (Companion)
In this paper we present the use of a previously developed single-objective optimization approach, together with the e-constraint method, to provide an approximation of the Pareto front in a multiobjective optimization problem. This approximation is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7cb9f4646c32c168c48840ca82fb35e4
https://doi.org/10.1145/1274000.1274052
https://doi.org/10.1145/1274000.1274052