Bioinspired Tabu Search for Geographic Partitioning

  • Bernabe-Loranca, María B.
  • González-Velazquez, Rogelio
  • Estrada-Analco, María
  • Ruiz-Vanoye, Jorge A.
  • Fuentes-Penna, Alejandro
  • Sánchez, Abraham
Abstract:
The analytical observation of nature induces inspiration to propose new computational paradigms to create algorithms that solve optimization and artificial intelligence problems. The artificial vision allows establishing a problem with intelligent techniques from living systems. The bioinspired systems are presented as a set of models that are based on the behavior and the way of acting of some biological systems. These models can be expressed in data mining and operations research where the clustering is a recurrent technique in the P-median problem and territorial design. On this point, we have solved clustering problems using parti tioning with bioinspired aspects and variable neighborhood search to approximate optimal solutions. In this work we have improved the search strategy: we present a bioinspired partitioning algorithm with optimization by tabu search (TS). This clustering problem under a bioinspired connotation has been proposed after observing some characteristics in common between clustering and human behavior in conflict situations, where some characteristics have been modeled.
Research areas:
Year:
2017
Type of Publication:
In Book
Editor:
Nelishia Pillay, Andries P. Engelbrecht, Ajith Abraham, Mathys C. du Plessis, Václav Snášel, Azah Kamilah Muda
Volume:
419
Chapter:
17
Pages:
189-199
Publisher:
Springer International Publishing Switzerland
Series:
Advances in Intelligent Systems and Computing
ISBN:
978-3-319-27399-0
DOI:
10.1007/978-3-319-27400-3_17
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