Geodesic
Two methods for minimizing convex functions in a class of nonconvex sets
Žurnal vyčislitelʹnoj matematiki i matematičeskoj fiziki, Tome 48 (2008) no. 10, pp. 1802-1811 Cet article a éte moissonné depuis la source Math-Net.Ru

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The conditional gradient method and the steepest descent method, which are conventionally used for solving convex programming problems, are extended to the case where the feasible set is the set-theoretic difference between a convex set and the union of several convex sets. Iterative algorithms are proposed, and their convergence is examined. 
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Yu. A. Chernyaev. Two methods for minimizing convex functions in a class of nonconvex sets. Žurnal vyčislitelʹnoj matematiki i matematičeskoj fiziki, Tome 48 (2008) no. 10, pp. 1802-1811. http://geodesic.mathdoc.fr/item/ZVMMF_2008_48_10_a3/

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