A Biased Random Key Genetic Algorithm to Solve the Transmission Expansion Planning Problem with Re-design

Abstract

Most developing countries need to constantly work on the expansion of their electric transmission networks. This task needs to be carefully planned. Unlike several Network Design Problem, a transmission network may become more efficient after cutting-off some of its transmission lines. The version of the problem where the redesign is allowed when expanding is known in the literature as Transmission Expansion Planning Problem with Re-design, TEPr, and will be the focus of this paper. To solve TEPr, we propose a hybridization of Biased Random-Key Genetic Algorithm with Local Branching. Computational experiments showed the impact of the developed method in comparison to the straight forward application of the mathematical formulation.