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Beam-ACO based on stochastic sampling for makespan optimization concerning the TSP with time windows
conference contribution
posted on 2009-07-23, 00:00 authored by M López-Ibáñez, C Blum, Dhananjay ThiruvadyDhananjay Thiruvady, A T Ernst, B MeyerThe 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. © Springer-Verlag Berlin Heidelberg 2009.
History
Event
EvoCOP (Conference) (9th : 2009 : Tübingen, Germany)Volume
5482Series
Lecture Notes in Computer Science; v.5482Pagination
97 - 108Publisher
SpringerLocation
Tübingen, GermanyPlace of publication
Berlin, GermanyPublisher DOI
Start date
2009-04-15End date
2009-04-17ISSN
0302-9743eISSN
1611-3349ISBN-13
9783642010088ISBN-10
3642010083Language
engPublication classification
E1.1 Full written paper - refereedTitle of proceedings
Evolutionary computation in combinatorial optimization : 9th European Conference, EvoCOP 2009, Tübingen, Germany, April 15-17, 2009 ; proceedingsUsage metrics
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