Using simulated annealing to design good codes
IEEE Transactions on Information Theory
Stochastic Local Search Algorithms for DNA Word Design
DNA8 Revised Papers from the 8th International Workshop on DNA Based Computers: DNA Computing
Evaluating las vegas algorithms: pitfalls and remedies
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Linear constructions for DNA codes
Theoretical Computer Science
A Framework for Designing Novel Magnetic Tiles Capable of Complex Self-assemblies
UC '08 Proceedings of the 7th international conference on Unconventional Computing
Randomized fast design of short DNA words
ACM Transactions on Algorithms (TALG)
Dynamic neighborhood searches for thermodynamically designing DNA sequence
DNA13'07 Proceedings of the 13th international conference on DNA computing
Randomized fast design of short DNA words
ICALP'05 Proceedings of the 32nd international conference on Automata, Languages and Programming
DNA sequence design by dynamic neighborhood searches
DNA'06 Proceedings of the 12th international conference on DNA Computing
Deterministic polynomial-time algorithms for designing short DNA words
TAMC'10 Proceedings of the 7th annual conference on Theory and Applications of Models of Computation
Flexible word design and graph labeling
ISAAC'06 Proceedings of the 17th international conference on Algorithms and Computation
Towards a population-based framework for improving stochastic local search algorithms
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Deterministic polynomial-time algorithms for designing short DNA words
Theoretical Computer Science
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Sets of DNA strands that satisfy combinatorial constraints play an important role in various approaches to biomolecular computation, nanostructure design, and molecular tagging. The problem of designing such sets of DNA strands, also known as the DNA code design problem, appears to be computationally hard. In this paper, we show how a recently proposed stochastic local search algorithm for DNA code design can be improved by using hybrid, randomised neighbourhoods. This new type of neighbourhoods tructure equally supports small changes to a given candidate set of strands as well as much larger modifications, which correspondt o random, long range connections in the search space induced by the standard (1-mutation) neighbourhood. We report several cases in which our algorithm finds word sets that match or exceed the best previously known constructions.