The Chaos-Based Approaches for Actual Metaheuristic Algorithms
Abstract
Along with rapid developments in computational technologies,
evolutionary/heuristic/metaheuristic algorithms have frequently become used in
many applications to solve optimization problems. Nowadays, new algorithms are
being developed and improvements have been made to existing algorithms. In this
study, chaos-based modifications have been proposed for recently introduced metaheuristic
algorithms: Backtracking Search (BS), Grey Wolf Optimizer (GWO) and Vortex
Search (VS), and the algorithms have been analyzed by detailed comparisons. The
proposed approaches are based on generating new values through chaos maps,
rather than some random numbers normally used in the algorithms, to improve
their solutions. In addition, some modifications are performed to the
structural operations of the algorithms used in the optimization process by
taking advantage of chaos-based values. The performances of the algorithms are
evaluated by considering two metrics: convergence rates and statistical
results. Experiments demonstrated that the performance of the algorithms with
the proposed modifications based on the chaos approach, are better than, or at least comparable to,
the original algorithms.
Keywords
References
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Details
Primary Language
English
Subjects
Engineering
Journal Section
Research Article
Publication Date
December 31, 2018
Submission Date
May 2, 2018
Acceptance Date
October 17, 2018
Published in Issue
Year 2018 Volume: 23 Number: 3