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Soft Computing

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27.09.2016 | Methodologies and Application

Dynamic differential evolution with combined variants and a repair method to solve dynamic constrained optimization problems: an empirical study

verfasst von: María-Yaneli Ameca-Alducin, Efrén Mezura-Montes, Nicandro Cruz-Ramírez

Erschienen in: Soft Computing | Ausgabe 2/2018

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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.

Vorheriger Artikel Granular description of data in a non-stationary environment

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Titel: Dynamic differential evolution with combined variants and a repair method to solve dynamic constrained optimization problems: an empirical study
verfasst von: María-Yaneli Ameca-Alducin
Efrén Mezura-Montes
Nicandro Cruz-Ramírez
Publikationsdatum: 27.09.2016
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 2/2018
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-016-2353-1

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