Multiobjective Genetic Search for Spanning Tree Problem

  • Rajeev Kumar
  • P. K. Singh
  • P. P. Chakrabarti
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3316)

Abstract

A major challenge to solving multiobjective optimization problems is to capture possibly all the (representative) equivalent and diverse solutions at convergence. In this paper, we attempt to solve the generic multi-objective spanning tree (MOST) problem using an evolutionary algorithm (EA). We consider, without loss of generality, edge-cost and tree-diameter as the two objectives, and use a multiobjective evolutionary algorithm (MOEA) that produces diverse solutions without needing a priori knowledge of the solution space. We test this approach for generating (near-) optimal spanning trees, and compare the solutions obtained from other conventional approaches.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Rajeev Kumar
    • 1
  • P. K. Singh
    • 1
  • P. P. Chakrabarti
    • 1
  1. 1.Department of Computer Science and EngineeringIndian Institute of Technology KharagpurKharagpurIndia

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