D.C. programming approach for solving an applied ore-processing problem.

*(English)*Zbl 1412.90120Summary: This paper was motivated by a practical optimization problem formulated at the Erdenet Mining Corporation (Mongolia). By solving an identification problem for a chosen design of experiment we developed a quadratic model that quite adequately represents the experimental data. The problem obtained turned out to be the indefinite quadratic program, which we solved by applying the global search theory for a d.c. programming developed by A.S. Strekalovsky [in: Optimization in science and engineering. In honor of the 60th birthday of Panos M. Pardalos. New York, NY: Springer. 465–502 (2014; Zbl 1335.90075); Elements of nonconvex optimization. (Russian). Novosibirsk: Nauka (2003) ; Zh. Vychisl. Mat. Mat. Fiz. 43, No. 3, 399–409 (2003; Zbl 1103.26012); translation in Comput. Math. Math. Phys. 43, No. 3, 380–390 (2003)]. According to this d.c. optimization theory, we performed a local search that takes into account the structure of the problem in question, and constructed procedures of escaping critical points provided by the local search. The algorithms proposed for d.c. programming were verified using a set of test problems as well as a copper content maximization problem arising at the mining factory.

##### MSC:

90C26 | Nonconvex programming, global optimization |

90C90 | Applications of mathematical programming |

90C20 | Quadratic programming |

##### Keywords:

identification and modeling; nonconvex optimization; indefinite quadratic programming; difference of two convex functions; local and global searches
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\textit{R. Enkhbat} et al., J. Ind. Manag. Optim. 14, No. 2, 613--623 (2018; Zbl 1412.90120)

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##### References:

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