Abstract
This chapter will focus on the development of a system with Artificial Intelligence based on Evolutionary Computation that allow generate a quasi-optimum trace of a pipeline integrating Digital Elevation Models and Geographical Information Systems. The algorithm is conceived with optimization purposes based on the relevant characteristics of the trace without prior monetary quantification, although the last was taken into consideration.
The chapter will consist of three main sections: the description of the baseline information, a description of the design of evolutionary algorithm (EA) handling information of the first stage and finally the tasks of adjusting the parameters of EA and obtaining pipeline route quasi-optimum in the case of interest.
The tool developed in this chapter allows obtaining a quasi-optimal route trace by using a hybrid evolutionary algorithm. This development that exploits modern technologies opens new perspectives for feasibility studies of paths, reducing the total costs.
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Núñez Mc Leod, J.E., Rivera, S.S. (2013). Pipeline Trace Quasi-optimum Determination. In: Zelinka, I., Snášel, V., Abraham, A. (eds) Handbook of Optimization. Intelligent Systems Reference Library, vol 38. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30504-7_27
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DOI: https://doi.org/10.1007/978-3-642-30504-7_27
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