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Beam-ACO based on stochastic sampling: a case study on the TSP with time Windows

Author
López, M.; Blum, C.
Type of activity
Report
Date
2008-10
Code
LSI-08-28-R
Repository
http://hdl.handle.net/2117/86872 Open in new window
Abstract
Beam-ACO algorithms are hybrid methods that combine the metaheuristic ant colony optimization with beam search. They heavily rely on accurate and computationally inexpensive bounding information for choosing between different partial solutions during the solution construction process. In this work we present the use of stochastic sampling as a useful alternative to bounding information in cases were computing accurate bounding information is too expensive. As a case study we choose the well-know...
Citation
López, M., Blum, C. "Beam-ACO based on stochastic sampling: a case study on the TSP with time windows". 2008.
Keywords
Beam-ACO, Stochastic sampling, Travelling salesman problem with time windows
Group of research
ALBCOM - Algorithms, Computational Biology, Complexity and Formal Methods

Participants

  • López Ibañez, Manuel  (author)
  • Blum, Christian Clemens  (author)

Attachments