Network random keys - a tree representation scheme for genetic and evolutionary algorithms

Evolutionary Computation
Franz RothlaufArmin Heinzl

Abstract

When using genetic and evolutionary algorithms for network design, choosing a good representation scheme for the construction of the genotype is important for algorithm performance. One of the most common representation schemes for networks is the characteristic vector representation. However, with encoding trees, and using crossover and mutation, invalid individuals occur that are either under- or over-specified. When constructing the offspring or repairing the invalid individuals that do not represent a tree, it is impossible to distinguish between the importance of the links that should be used. These problems can be overcome by transferring the concept of random keys from scheduling and ordering problems to the encoding of trees. This paper investigates the performance of a simple genetic algorithm (SGA) using network random keys (NetKeys) for the one-max tree and a real-world problem. The comparison between the network random keys and the characteristic vector encoding shows that despite the effects of stealth mutation, which favors the characteristic vector representation, selectorecombinative SGAs with NetKeys have some advantages for small and easy optimization problems. With more complex problems, SGAs with network ran...Continue Reading

Citations

Nov 25, 2003·Evolutionary Computation·Franz Rothlauf, David E Goldberg
Jun 19, 2008·IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society·Jorge TavaresErnesto Costa
Oct 10, 2014·Evolutionary Computation·Carlos Eduardo de AndradeFlávio Keidi Miyazawa
Jun 4, 2014·TheScientificWorldJournal·Chun-Wei TsaiTzung-Pei Hong
Jun 24, 2005·IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society·Georg SchneiderEdgar Körner

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