The preservation of favored building blocks in the struggle for fitness: the puzzle algorithm
作者： A. Zaritsky , M. Sipper
关键词: Mathematics 、 Population 、 Artificial intelligence 、 Cooperative coevolution 、 Evolutionary computation 、 Evolutionary algorithm 、 Greedy algorithm 、 String (computer science) 、 Algorithm 、 Computational complexity theory 、 Genetic algorithm
摘要: The shortest common superstring (SCS) problem, known to be NP-complete, seeks the string that contains all strings from a given set. In this paper, we present novel coevolutionary algorithm-the Puzzle Algorithm-where population of building blocks coevolves alongside solutions. We show experimentally our algorithm outperforms standard genetic (GA) and benchmark greedy on instances SCS problem inspired by deoxyribonucleic acid (DNA) sequencing. next compare previously presented cooperative with Co-Puzzle Algorithm-the puzzle coupled coevolution-showing latter proves top gun. Finally, discuss benefits using approach in general field evolutionary algorithms.
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