Abstract
A class of nonconvex minimization problems can be classified as hidden convex minimization problems. A nonconvex minimization problem is called a hidden convex minimization problem if there exists an equivalent transformation such that the equivalent transformation of it is a convex minimization problem. Sufficient conditions that are independent of transformations are derived in this paper for identifying such a class of seemingly nonconvex minimization problems that are equivalent to convex minimization problems. Thus, a global optimality can be achieved for this class of hidden convex optimization problems by using local search methods. The results presented in this paper extend the reach of convex minimization by identifying its equivalent with a nonconvex representation.
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Li, D., Wu, ZY., Joseph Lee, HW. et al. Hidden Convex Minimization. J Glob Optim 31, 211–233 (2005). https://doi.org/10.1007/s10898-004-5697-5
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DOI: https://doi.org/10.1007/s10898-004-5697-5