Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Article type: Research Article
Authors: Guerine, Marcos* | Rosseti, Isabel | Plastino, Alexandre
Affiliations: Institute of Computing, Fluminense Federal University, Rua Passo da Pátria, Niterói, RJ, Brazil
Correspondence: [*] Corresponding author: Marcos Guerine, Institute of Computing, Fluminense Federal University, Av. Gal. Milton Tavares de Souza, s/n° - Bloco do Instituto de Computação, São Domingos, Niterói, 24210-346, RJ, Brazil, Tel: +55 27981268333; E-mail:mguerine@ic.uff.br
Abstract: The scope of this work is the application of data mining techniques to improve the performance of metaheuristics in the combinatorial optimization scenario. Data mining techniques have been coupled with metaheuristics in order to obtain patterns of suboptimal solutions that are used to guide the heuristic search for better-cost solutions in less computational time. This kind of hybridization has been successfully explored to solve several optimization problems, for which the solutions and their patterns are limitedly characterized by sets of elements. The challenge of this work is to extend this hybrid approach to a broader domain. We therefore propose a hybrid data mining heuristic to solve the one-commodity pickup-and-delivery traveling salesman problem, for which solutions are defined by sequences of elements. Computational experiments, conducted on a set of instances from the literature, showed that the hybrid heuristic reached better-costs solutions faster than the original strategy. This way, it was evidenced that not only problems whose solutions are represented by sets of elements can benefit from the hybridization of metaheuristics with data mining, but also problems whose solutions are represented by a sequence of elements.
Keywords: Hybrid metaheuristics, data mining, GRASP, 1-PDTSP
DOI: 10.3233/IDA-160860
Journal: Intelligent Data Analysis, vol. 20, no. 5, pp. 1133-1156, 2016
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
sales@iospress.com
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
info@iospress.nl
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office info@iospress.nl
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
china@iospress.cn
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
如果您在出版方面需要帮助或有任何建, 件至: editorial@iospress.nl