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)


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.


Evolutionary Algorithm Span Tree Multiobjective Optimization Network Design Problem Multiobjective Optimization Problem 
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 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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