Orientation matters: how to efficiently solve ocst problems with problem-specific EAs
Proceedings of the 10th annual conference on Genetic and evolutionary computation
New insights into the OCST problem: integrating node degrees and their location in the graph
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
The property analysis of evolutionary algorithms applied to spanning tree problems
Applied Intelligence
A memetic algorithm for the optimum communication spanning tree problem
HM'07 Proceedings of the 4th international conference on Hybrid metaheuristics
Solving OCST problems with problem-specific guided local search
Proceedings of the 12th annual conference on Genetic and evolutionary computation
New hybrid genetic algorithm for solving optimal communication spanning tree problem
Proceedings of the 2011 ACM Symposium on Applied Computing
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This paper deals with the Optimum Communication Spanning Tree Problem (OCST) which is well known as an NP-hard problem. For solving the problem, we uses an evolutionary approach. This paper presents a new effective tree encoding and proposes a tree construction routine (TCR) to generate a tree from the encoding. The basic principle is to break a cycle. We also propose a new crossover operator that focuses on the inheritance of parental information and the use of network information. Consequently, we confirm that the proposed algorithm is superior to other algorithms applied to the OCST problem or other tree problems. Moreover, our method can find a better solution than the solution which was previously known as the best solution. In addition, we analyzed the locality and diversity property of encoding and observed that the proposed method has high locality and at the same time it preserves population diversity for many generations. Finally, we conclude that these properties are the main reasons why the proposed method outperforms the other encodings.