Solving the sorting network problem using iterative optimization with evolved hypermutations
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
ICANNGA'09 Proceedings of the 9th international conference on Adaptive and natural computing algorithms
Efficient stochastic local search algorithm for solving the shortest common supersequence problem
Proceedings of the 12th annual conference on Genetic and evolutionary computation
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This paper presents benchmarking of a stochastic local search algorithm called Prototype Optimization with Evolved Improvement Steps (POEMS) on the BBOB 2010 noise-free functions testbed. An original version of the POEMS algorithm presented at BBOB 2009 workshop is compared to a new variant using a pool of candidate prototypes. Experiments for 2D, 3D, 5D, 10D and 20D were done. Experimental results show that the new variant of POEMS performs better on several functions for lower dimensions. Both variants perform equally on the 20D problems.