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 
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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Voir la notice de l'article provenant de la source Math-Net.Ru

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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[2] Chernyaev Yu. A., “Obobschenie metoda uslovnogo gradienta na odin klass nevypuklykh ekstremalnykh zadach”, Zh. vychisl. matem. i matem. fiz., 46:4 (2006), 576–582 | MR | Zbl

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