Novel Random Key Encoding Schemes for the Differential Evolution of Permutation Problems

Differential evolution is a powerful nature-inspired real-parameter optimization algorithm that has been successfully used to solve a number of hard optimization problems. It has been used to tackle both continuous and discrete optimization problems. The application of a continuous method to discret...

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Bibliographic Details
Published in:IEEE transactions on evolutionary computation 2022-02, Vol.26 (1), p.43-57
Main Authors: Kromer, Pavel, Uher, Vojtech, Snasel, Vaclav
Format: Article
Language:English
Subjects:
Decoding
Differential evolution (DE)
Dimensional analysis
Encoding
Evolutionary algorithms
Evolutionary computation
linear ordering problem (LOP)
Optimization
Permutations
random key (RK) encoding
Search problems
search space analysis
Sociology
Solution space
Statistics
Traveling salesman problem
traveling salesman problem (TSP)
Traveling salesman problems
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Summary:Differential evolution is a powerful nature-inspired real-parameter optimization algorithm that has been successfully used to solve a number of hard optimization problems. It has been used to tackle both continuous and discrete optimization problems. The application of a continuous method to discrete problems involves several challenges, including solution representation and search space-solution space mapping. In this work, we study random key encoding, a popular encoding scheme that is used to represent permutations in high-dimensional continuous spaces. We analyze the search space it constitutes, study its structure and properties, and introduce two novel modifications of the encoding. We investigate the proposed encoding strategies in the context of four variants of the differential evolution algorithm and demonstrate their usefulness for two widespread permutation problems: 1) the linear ordering problem and 2) the traveling salesman problem.
ISSN:1089-778X
1941-0026
DOI:10.1109/TEVC.2021.3087802