Solving the sorting network problem using iterative optimization with evolved hypermutations
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
A new local search algorithm for the DNA fragment assembly problem
EvoCOP'07 Proceedings of the 7th European conference on Evolutionary computation in combinatorial optimization
ICANNGA'09 Proceedings of the 9th international conference on Adaptive and natural computing algorithms
Bee algorithms for solving DNA fragment assembly problem with noisy and noiseless data
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Benchmark datasets for the DNA fragment assembly problem
International Journal of Bio-Inspired Computation
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The paper presents a successful application of an evolutionary based iterative optimization method called Prototype Optimization with Evolved Improvement Steps (POEMS) to the DNA fragment assembly problem. The DNA fragment assembly problem, known to be NP-hard, is of great importance as it constitutes an important step in the genome project. The POEMS is an iterative algorithm that employs an evolutionary algorithm for exploration of the current solution's neighborhood in each iteration of the optimization process. Experiments show that the proposed POEMS approach performs very well and generates better results than those generated by other state-of-the-art methods.