A Variable Neighborhood Search Algorithm for Solving the Steiner Minimal Tree Problem in Sparse Graphs

Abstract

Steiner Minimal Tree (SMT) is a complex optimization problem that has many important applications in science and technology; This is a NP-hard problem. Much research has been carried out to solve the SMT problem using approximate algorithms. This paper presents A Variable Neighborhood Search (VNS) algorithm for solving the SMT problem in sparse graphs; The proposed algorithm has been tested on sparse graphs in a standardized experimental data system, and it yields better results than some other heuristic algorithms.

Authors and Affiliations

C. V. Tran, N. H. Ha

Keywords

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  • EP ID EP45811
  • DOI http://dx.doi.org/10.4108/eai.6-2-2019.156534
  • Views 178
  • Downloads 0

How To Cite

C. V. Tran, N. H. Ha (2018). A Variable Neighborhood Search Algorithm for Solving the Steiner Minimal Tree Problem in Sparse Graphs. EAI Endorsed Transactions on Context-aware Systems and Applications, 5(15), -. https://europub.co.uk/articles/-A-45811