A Variable Neighborhood Search Algorithm for Solving the Steiner Minimal Tree Problem in Sparse Graphs
Journal Title: EAI Endorsed Transactions on Context-aware Systems and Applications - Year 2018, Vol 5, Issue 15
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 285
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