A hyperheuristic approach based on low-level heuristics for the travelling thief problem
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @Article{ElYafrani:GPEM:TTP,
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author = "Mohamed {El Yafrani} and Marcella Martins and
Markus Wagner and Belaid Ahiod and Myriam Delgado and
Ricardo Luders",
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title = "A hyperheuristic approach based on low-level
heuristics for the travelling thief problem",
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journal = "Genetic Programming and Evolvable Machines",
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year = "2018",
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volume = "19",
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number = "1-2",
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pages = "121--150",
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month = jun,
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note = "Special Issue on Automated Design and Adaptation of
Heuristics for Scheduling and Combinatorial
Optimisation",
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keywords = "genetic algorithms, genetic programming, Heuristic
selection, Travelling thief problem, Multi-component
problems",
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ISSN = "1389-2576",
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DOI = "doi:10.1007/s10710-017-9308-x",
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abstract = "In this paper, we investigate the use of
hyper-heuristics for the travelling thief problem
(TTP). TTP is a multi-component problem, which means it
has a composite structure. The problem is a combination
between the travelling salesman problem and the
knapsack problem. Many heuristics were proposed to deal
with the two components of the problem separately. In
this work, we investigate the use of automatic online
heuristic selection in order to find the best
combination of the different known heuristics. In order
to achieve this, we propose a genetic programming based
hyper-heuristic called GPHS*, and compare it to
state-of-the-art algorithms. The experimental results
show that the approach is competitive with those
algorithms on small and mid-sized TTP instances.",
- }
Genetic Programming entries for
Mohamed El Yafrani
Marcella Scoczynski Ribeiro Martins
Markus Wagner
Belaid Ahiod
Myriam Regattieri De Biase da Silva Delgado
Ricardo Luders
Citations