Comparative studies on nonconvex optimization methods fortransmission network expansion planning

摘要

We have investigated and extensively tested three families ofnnonconvex optimization approaches for solving the transmission networknexpansion planning problem: simulated annealing (SA), genetic algorithmsn(GA), and tabu search algorithms (TS). The paper compares the mainnfeatures of the three approaches and presents an integrated view ofnthese methodologies. A hybrid approach is then proposed which presentsnperformances which are far better than the ones obtained with any ofnthese approaches individually. Results obtained in tests performed withnlarge scale real-life networks are summarized