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Beam-ACO based on stochastic sampling for makespan optimization concerning the TSP with time windows

journal contribution
posted on 2024-11-01, 13:25 authored by Manuel Ibanez, Christian Blum, Dhananjay Thiruvady, Andreas Tilman Ernst, Bernard Meyer
The travelling salesman problem with time windows is a difficult optimization problem that appears, for example, in logistics. Among the possible objective functions we chose the optimization of the makespan. For solving this problem we propose a so-called Beam-ACO algorithm, which is a hybrid method that combines ant colony optimization with beam search. In general, Beam-ACO algorithms heavily rely on accurate and computationally inexpensive bounding information for differentiating between partial solutions. In this work we use stochastic sampling as an alternative to bounding information. Our results clearly demonstrate that the proposed algorithm is currently a state-of-the-art method for the tackled problem.

History

Related Materials

  1. 1.
    DOI - Is published in 10.1007/978-3-642-01009-5_9
  2. 2.
    ISSN - Is published in 03029743

Journal

Lecture Notes in Computer Science

Volume

5482

Start page

97

End page

108

Total pages

12

Publisher

Springer

Place published

Berlin, Germany

Language

English

Copyright

© 2009 Springer Berlin Heidelberg

Former Identifier

2006041577

Esploro creation date

2020-06-22

Fedora creation date

2015-01-16

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