Optimization in the migration problem of mobile agents in distributed information retrieval systems

Yan Xiang He, Yi Feng Chen, Jing He, Jiannong Cao

Research output: Journal article publicationJournal articleAcademic researchpeer-review

1 Citation (Scopus)

Abstract

We employ genetic algorithms to solve the migration problem (MP). We propose a new encoding scheme to represent trees, which is composed of two parts: the pre-ordered traversal sequence of tree vertices and the children number sequence of corresponding tree vertices. The proposed encoding scheme has the advantages of simplicity for encoding and decoding, ease for GA operations, and better equilibrium between exploration and exploitation. It is also adaptive in that, with few restrictions on the length of code, it can be freely lengthened or shortened according to the characteristics of the problem space. Furthermore, the encoding scheme is highly applicable to the degree-constrained minimum spanning tree problem because it also contains the degree information of each node. The simulation results demonstrate the higher performance of our algorithm, with fast convergence to the optima or sub-optima on various problem sizes. Compared with the binary string encoding of vertices, when the problem size is large, our algorithm runs remarkably faster with comparable search capability.
Original languageEnglish
Pages (from-to)153-160
Number of pages8
JournalWuhan University Journal of Natural Sciences
Volume9
Issue number2
Publication statusPublished - 1 Mar 2004

Keywords

  • Distributed information retrieval
  • Genetic algorithms
  • Migration problem
  • Mobile agents

ASJC Scopus subject areas

  • General

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