A hybrid grouping genetic algorithm for the registration area planning problem

  • Authors:

  • Tabitha James;Mark Vroblefski;Quinton Nottingham

  • Affiliations:

  • Department of Business Information Technology, Pamplin College of Business, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA;Department of Management Information Systems, Eller College of Management, University of Arizona, Tucson, AZ 85721, USA;Department of Business Information Technology, Pamplin College of Business, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA

  • Venue:
  • Computer Communications
  • Year:
  • 2007

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Abstract

With the growing use of mobile communication devices, the management of such technologies is of increasing importance. The registration area planning (RAP) problem examines the grouping of cells comprising a personal communication services (PCS) network into contiguous blocks in an effort to reduce the cost of managing the location of the devices operating on the network, in terms of bandwidth. This study introduces a hybridized grouping genetic algorithm (HGGA) to obtain cell formations for the RAP problem. The hybridization is accomplished by adding a tabu search-based improvement operator to a traditional grouping genetic algorithm (GGA). Results indicate that significant performance gains can be realized by hybridizing the algorithm, especially for larger problem instances. The HGGA is shown to consistently outperform the traditional GGA on problems of size greater than 19 cells.