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Corridor Selection and Fine Tuning for the Corridor Method

  • Marco Caserta
  • Stefan Voß
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5851)

Abstract

In this paper we present a novel hybrid algorithm, in which ideas from the genetic algorithm and the GRASP metaheuristic are cooperatively used and intertwined to dynamically adjust a key parameter of the corridor method, i.e., the corridor width, during the search process. In addition, a fine-tuning technique for the corridor method is then presented. The response surface methodology is employed in order to determine a good set of parameter values given a specific problem input size. The effectiveness of both the algorithm and the validation of the fine tuning technique are illustrated on a specific problem selected from the domain of container terminal logistics, known as the blocks relocation problem, where one wants to retrieve a set of blocks from a bay in a specified order, while minimizing the overall number of movements and relocations. Computational results on 160 benchmark instances attest the quality of the algorithm and validate the fine tuning process.

Keywords

Response Surface Methodology Fine Tune Incumbent Solution Target Block Elite Solution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Marco Caserta
    • 1
  • Stefan Voß
    • 1
  1. 1.Institute of Information SystemsUniversity of HamburgHamburgGermany

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