Beam-ACO-hybridizing ant colony optimization with beam search: an application to open shop scheduling [An article from: Computers and Operations Research] Buy on Amazon

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Beam-ACO-hybridizing ant colony optimization with beam search: an application to open shop scheduling [An article from: Computers and Operations Research]

AuthorC. Blum
PublisherElsevier
7.95 USD
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Book Details

Author(s)C. Blum
PublisherElsevier
ISBN / ASINB000RR48BI
ISBN-13978B000RR48B2
AvailabilityAvailable for download now
Sales Rank99,999,999
MarketplaceUnited States  🇺🇸

Description

This digital document is a journal article from Computers and Operations Research, published by Elsevier in 2005. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

Description:
Ant colony optimization (ACO) is a metaheuristic approach to tackle hard combinatorial optimization problems. The basic component of ACO is a probabilistic solution construction mechanism. Due to its constructive nature, ACO can be regarded as a tree search method. Based on this observation, we hybridize the solution construction mechanism of ACO with beam search, which is a well-known tree search method. We call this approach Beam-ACO. The usefulness of Beam-ACO is demonstrated by its application to open shop scheduling (OSS). We experimentally show that Beam-ACO is a state-of-the-art method for OSS by comparing the obtained results to the best available methods on a wide range of benchmark instances.
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