Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/118681
Citations | ||
Scopus | Web of Science® | Altmetric |
---|---|---|
?
|
?
|
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ameca-Alducin, M. | - |
dc.contributor.author | Mezura-Montes, E. | - |
dc.contributor.author | Cruz-Ramírez, N. | - |
dc.date.issued | 2018 | - |
dc.identifier.citation | Soft Computing, 2018; 22(2):541-570 | - |
dc.identifier.issn | 1432-7643 | - |
dc.identifier.issn | 1433-7479 | - |
dc.identifier.uri | http://hdl.handle.net/2440/118681 | - |
dc.description.abstract | An empirical study of the algorithm dynamic differential evolution with combined variants with a repair method (DDECV + Repair) in the solution of dynamic constrained optimization problems is presented. Unexplored aspects of the algorithm are of particular interest in this work: (1) the role of each one of its elements, (2) its sensitivity to different change frequencies and change severities in the objective function and the constraints, (3) its ability to detect a change and recover after it, besides its diversity handling (percentage of feasible and infeasible solutions) during the search, and (4) its performance with dynamism present in different parts of the problem. Seven performance measures, eighteen recently proposed test problems and eight algorithms found in the specialized literature are considered in four experiments. The statistically validated results indicate that DDECV + Repair is robust to change frequency and severity variations, and that it is particularly fast to recover after a change in the environment, but highly depends on its repair method and its memory population to provide competitive results. DDECV + Repair shows evidence on the convenience of keeping a proportion of infeasible solutions in the population when solving dynamic constrained optimization problems. Finally, DDECV + Repair is highly competitive particularly when dynamism is present in both, objective function and constraints. | - |
dc.description.statementofresponsibility | María-Yaneli Ameca-Alducin, Efrén Mezura-Montes, Nicandro Cruz-Ramírez | - |
dc.language.iso | en | - |
dc.publisher | Springer | - |
dc.rights | © Springer-Verlag Berlin Heidelberg 2016 | - |
dc.source.uri | http://dx.doi.org/10.1007/s00500-016-2353-1 | - |
dc.subject | Differential evolution; constraint handling; dynamic optimization; dynamic constrained optimization problem | - |
dc.title | Dynamic differential evolution with combined variants and a repair method to solve dynamic constrained optimization problems: an empirical study | - |
dc.type | Journal article | - |
dc.identifier.doi | 10.1007/s00500-016-2353-1 | - |
dc.relation.grant | 220522 | - |
dc.relation.grant | 250141 | - |
pubs.publication-status | Published | - |
dc.identifier.orcid | Ameca-Alducin, M. [0000-0002-0099-9032] | - |
Appears in Collections: | Aurora harvest 4 Computer Science publications |
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.