A hyperheuristic approach based on low-level heuristics for the travelling thief problem

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@Article{ElYafrani:GPEM:TTP,
  author =       "Mohamed {El Yafrani} and Marcella Martins and 
                 Markus Wagner and Belaid Ahiod and Myriam Delgado and 
                 Ricardo Luders",
  title =        "A hyperheuristic approach based on low-level
                 heuristics for the travelling thief problem",
  journal =      "Genetic Programming and Evolvable Machines",
  note =         "Online first",
  keywords =     "genetic algorithms, genetic programming, Heuristic
                 selection, Travelling thief problem, Multi-component
                 problems",
  ISSN =         "1389-2576",
  DOI =          "doi:10.1007/s10710-017-9308-x",
  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