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Combinatorial Optimization Problems in Geometric Settings
Combinatorial Optimization Problems in Geometric Settings
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Combinatorial Optimization Problems In Geometric Settings arise in several areas of Network Design such as positioning of cell phone towers or other sensors to provide coverage to the area of interest. These problems can typically be formulated as some version of geometric set cover such as clustering, facility. In a non-geometric setting all these problems would typically be hard to solve. The underlying geometry can at times be exploited, however, to find efficient approximate solutions.
  • Leidėjas:
  • Metai: 2013
  • Puslapiai: 124
  • ISBN-10: 3639700589
  • ISBN-13: 9783639700589
  • Formatas: 15.2 x 22.9 x 0.7 cm, minkšti viršeliai
  • Kalba: Anglų

Combinatorial Optimization Problems in Geometric Settings (el. knyga) (skaityta knyga) | knygos.lt

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Combinatorial Optimization Problems In Geometric Settings arise in several areas of Network Design such as positioning of cell phone towers or other sensors to provide coverage to the area of interest. These problems can typically be formulated as some version of geometric set cover such as clustering, facility. In a non-geometric setting all these problems would typically be hard to solve. The underlying geometry can at times be exploited, however, to find efficient approximate solutions.

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  • Autorius: Gaurav Kanade
  • Leidėjas:
  • Metai: 2013
  • Puslapiai: 124
  • ISBN-10: 3639700589
  • ISBN-13: 9783639700589
  • Formatas: 15.2 x 22.9 x 0.7 cm, minkšti viršeliai
  • Kalba: Anglų

Combinatorial Optimization Problems In Geometric Settings arise in several areas of Network Design such as positioning of cell phone towers or other sensors to provide coverage to the area of interest. These problems can typically be formulated as some version of geometric set cover such as clustering, facility. In a non-geometric setting all these problems would typically be hard to solve. The underlying geometry can at times be exploited, however, to find efficient approximate solutions.

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