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A homogeneous predictor-corrector algorithm for stochastic nonsymmetric convex conic optimization with discrete support | ||
| Communications in Combinatorics and Optimization | ||
| مقاله 8، دوره 8، شماره 3، آذر 2023، صفحه 531-559 اصل مقاله (410.39 K) | ||
| نوع مقاله: Original paper | ||
| شناسه دیجیتال (DOI): 10.22049/cco.2022.27449.1266 | ||
| نویسندگان | ||
| Baha Alzalg* 1؛ Mohammad Alabedalhadi2 | ||
| 1Department of Mathematics, The University of Jordan. | ||
| 2Math Dept, Balqa Applied University | ||
| چکیده | ||
| We consider a stochastic convex optimization problem over nonsymmetric cones with discrete support. This class of optimization problems has not been studied yet. By using a logarithmically homogeneous self-concordant barrier function, we present a homogeneous predictor-corrector interior-point algorithm for solving stochastic nonsymmetric conic optimization problems. We also derive an iteration bound for the proposed algorithm. Our main result is that we uniquely combine a nonsymmetric algorithm with efficient methods for computing the predictor and corrector directions. Finally, we describe a realistic application and present computational results for instances of the stochastic facility location problem formulated as a stochastic nonsymmetric convex conic optimization problem. | ||
| کلیدواژهها | ||
| Convex optimization؛ Nonsymmetric programming؛ Stochastic programming؛ Predictor-corrector methods؛ Interior-point methods | ||
| مراجع | ||
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