An Effective Representation Scheme in Multifactorial Evolutionary Algorithm for Solving Cluster Shortest-Path Tree Problem

The wide range of applications of Cluster Tree Problems has been motivating extensive research into various algorithms and techniques with a view to promoting both efficiency of the solving and qualities of solutions. A representative of Cluster Tree Problems, the Cluster Shortest-Path Tree Problem (CSTP) arose from the practical need to optimize network systems such as irrigation systems, network cables and distribution systems. In this paper, we proposed the Multifactorial Evolutionary Algorithm (MFEA) to approach the CSTP with a representation scheme based on the Cayley Code. The proposed algorithm exploit advantages of Cayley Code for improving the MFEAs performance and quality solutions. This approach also applied new decoding method to transform the solution from the unified search space to the tasks. Experiments were conducted to compare the performances of the proposed to another approximation algorithm on various set of instances. The experimental results show that proposed algorithm surpass existing algorithm on almost test cases.

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