Parallelization Clonal Selection Algorithm with MPI.NET for Optimization Problem
Ayi Purbasari1, Achmad Nizar Hidayanto2, Arief Zulianto3

1Ayi Purbasari, Department Informatic, Universitas Pasundan, Bandung, Indonesia.

2Achmad Nizar Hidayanto, Department of Computer Science, Jakarta, Indonesia.

3Arief Zulianto, Department of Informatic, Universitas Langlangbuana, Bandung, Indonesia

Manuscript received on 05 June 2019 | Revised Manuscript received on 12 June 2019 | Manuscript Published on 19 June 2019 | PP: 184-191 | Volume-8 Issue-8S June 2019 | Retrieval Number: H10310688S19/19©BEIESP

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Abstract: The idea of immune system as a computing inspiration has given rise to the Artificial Immune System (AIS). AIS has contributed in the field of optimization of complex issues, one of which is a clonal selection algorithm (CSA) for solving the Optimization Problem such as Traveling Salesperson Problems (TSP). Parallel characteristic inherently possessed by the immune system, provided an opportunity to give parallel computing to achieve better computational performance. The study resulted in two parallel models for the clonal selection algorithm. First model is a master-slave model, there is a master process that controls all communication. In the second model, all processes equivalent and communicate with each other. Both models are prepared to be built in system development with parallel environment using Visual C# language with MPI.NET framework. For both datasets, experiment gave consistent results. Model 1 is superior in getting the best-tour’s cost, although obtained with longer execution time, compared with Model 2. However, Model 2 is superior in less execution time needed.

Keywords: Clonal Selection Algorithm; CSA; Parallel Clonal Selection Algorithm; Message Passing Model; MPI.NET; TSP.
Scope of the Article: Sequential, Parallel and Distributed Algorithms and Data Structures