Abstract
In this article, we present a new algorithm for the solution of nonconvex mixed-integer nonlinear optimization problems together with an application from gas network optimization, the gas transport energy cost minimization problem. Here, the aim is to transport gas through the network at minimum operating cost. The proposed algorithm is based on the adaptive refinement of a new class of MIP-relaxations and has been developed within an industry project on gas network optimization. Since therefore the implementation is not as general as it could be, our computational results are restricted to instances from gas network optimization at this point of time. However, as these problems are real-world applications and turn out to be rather hard to solve with the aid of state-of-the-art MINLP-solvers we believe that our computational results reveal the potential of this new approach and motivate further research on the presented techniques.
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Acknowledgements
The authors are grateful to Alexander Martin for fruitful discussions and comments. We thank our industry partner Open Grid Europe GmbH and the other partners of the ForNe project. The work was partially funded by the German Federal Ministry of Economics and Technology under grant number 0328006B.
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Geißler, B., Morsi, A., Schewe, L. (2013). A New Algorithm for MINLP Applied to Gas Transport Energy Cost Minimization. In: Jünger, M., Reinelt, G. (eds) Facets of Combinatorial Optimization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38189-8_14
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DOI: https://doi.org/10.1007/978-3-642-38189-8_14
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