Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1)
Bundle Enrichment Method for Nonsmooth Difference of Convex Programming Problems
Julkaisun tekijät: Gaudioso Manlio, Taheri Sona, Bagirov Adil M., Karmitsa Napsu
Kustantaja: MDPI
Julkaisuvuosi: 2023
Journal: Algorithms
Tietokannassa oleva lehden nimi: ALGORITHMS
Lehden akronyymi: ALGORITHMS
Artikkelin numero: 394
Volyymi: 16
Julkaisunumero: 8
Sivujen määrä: 21
eISSN: 1999-4893
DOI: http://dx.doi.org/10.3390/a16080394
Verkko-osoite: https://www.mdpi.com/1999-4893/16/8/394
Rinnakkaistallenteen osoite: https://research.utu.fi/converis/portal/detail/Publication/181176791
The Bundle Enrichment Method (BEM-DC) is introduced for solving nonsmooth difference of convex (DC) programming problems. The novelty of the method consists of the dynamic management of the bundle. More specifically, a DC model, being the difference of two convex piecewise affine functions, is formulated. The (global) minimization of the model is tackled by solving a set of convex problems whose cardinality depends on the number of linearizations adopted to approximate the second DC component function. The new bundle management policy distributes the information coming from previous iterations to separately model the DC components of the objective function. Such a distribution is driven by the sign of linearization errors. If the displacement suggested by the model minimization provides no sufficient decrease of the objective function, then the temporary enrichment of the cutting plane approximation of just the first DC component function takes place until either the termination of the algorithm is certified or a sufficient decrease is achieved. The convergence of the BEM-DC method is studied, and computational results on a set of academic test problems with nonsmooth DC objective functions are provided.
Ladattava julkaisu This is an electronic reprint of the original article. |  |
