Dot Net Platform for Distributed Evolutionary Algorithms with Application in Hydroinformatics

Author:

Stojanović Boban1,Milivojević Nikola2,Ivanović Miloš1,Divac Dejan2

Affiliation:

1. Faculty of Science, University of Kragujevac, Serbia

2. “Jaroslav Černi” Institute for the Development of Water Resources, Serbia

Abstract

Real-world problems often contain nonlinearities, relationships, and uncertainties that are too complex to be modeled analytically. In these scenarios, simulation-based optimization is a powerful tool to determine optimal system parameters. Evolutionary Algorithms (EAs) are robust and powerful techniques for optimization of complex systems that perfectly fit into this concept. Since evolutionary algorithms require a large number of time expensive evaluations of candidate solutions, the whole process of optimization can take huge CPU time. In this chapter, .NET platform for distributed evaluation using WCF (Windows Communication Foundation) Web services is presented in order to reduce computational time. This concept provides parallelization of evolutionary algorithms independently of geographic location and platform where evaluation is performed. Hydroinformatics is a typical representative of fields where complex systems with many uncertainties are studied. Application of the developed platform in hydroinformatics is also presented in this chapter.

Publisher

IGI Global

Reference37 articles.

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4. Bernal, A., Ramirez, M. A., Castro, H., Walteros, J. L., & Medaglia, A. L. (2009). JG2A: A grid-enabled object-oriented framework for developing genetic algorithms. In Proceedings of 2009 Systems and Information Engineering Design Symposium. Retrieved from http://www.scopus.com/inward/record.url?eid=2-s2.0-77950273380&partnerID=40&md5=1308cf163301b8874f9b64363989f0b1

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