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D.C. Constrained Optimization Approach for Solving Metal Recovery Processing Problem

  • Rentsen Enkhbat
  • Tatiana V. GruzdevaEmail author
  • Jamsranjav Enkhbayr
Conference paper
  • 201 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 12095)

Abstract

This paper was motivated by an industrial optimization problem arisen at the Erdenet Mining Corporation (Mongolia). The problem involved real industrial data turned out to be a quadratically constrained quadratic programming problem, which we solve by applying the global search theory for general DC programming. According to the theory, first, we obtain an explicit DC representation of the nonconvex functions involved in the problem. Second, we perform a local search that takes into account the structure of the problem in question. Further, we construct procedures for escaping critical points provided by the local search method. In particular, we propose a new way of constructing an approximation of the level set based on conjugated vectors. The computational simulation demonstrates that the proposed method is a quite flexible tool which can fast provide operations staff with good solutions to achieve the best performance according to specific requirements.

Keywords

DC programming Quadratic programming Inequality constraints Manufacturing processes Linearized problem Local search Global search 

Notes

Acknowledgements

This work supported by the project “ P2019-3751” of National University of Mongolia.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Institute of Mathematics and Digital Technology, Mongolian Academy of SciencesUlaanbaatarMongolia
  2. 2.Matrosov Institute for System Dynamics and Control Theory of SB of RASIrkutskRussia
  3. 3.National University of MongoliaUlaanbaatarMongolia

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