TY - CHAP
T1 - DNA computing and its application
AU - Watada, Junzo
PY - 2008
Y1 - 2008
N2 - The objectives of this Chapter are twofold: firstly to introduce DNA computation, and secondly to demonstrate how DNA computing can be applied to solve large, complex combinatorial problems, such as the optimal scheduling of a group of elevators servicing a number of floors in a multi-storey building. Recently, molecular (or wet) computing has been widely researched not only within the context of solving NP-complete/NP-hard problems -which are the most difficult problems in NP -but also implementation by way of digital (silicon-based) computers [23]. We commence with a description of the basic concepts of 'wet computation', then present recent results for the efficient management of a group of elevators.
AB - The objectives of this Chapter are twofold: firstly to introduce DNA computation, and secondly to demonstrate how DNA computing can be applied to solve large, complex combinatorial problems, such as the optimal scheduling of a group of elevators servicing a number of floors in a multi-storey building. Recently, molecular (or wet) computing has been widely researched not only within the context of solving NP-complete/NP-hard problems -which are the most difficult problems in NP -but also implementation by way of digital (silicon-based) computers [23]. We commence with a description of the basic concepts of 'wet computation', then present recent results for the efficient management of a group of elevators.
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U2 - 10.1007/978-3-540-78293-3_24
DO - 10.1007/978-3-540-78293-3_24
M3 - Chapter
AN - SCOPUS:44849104282
SN - 9783540782926
VL - 115
T3 - Studies in Computational Intelligence
SP - 1065
EP - 1089
BT - Studies in Computational Intelligence
ER -