D.C. Constrained Optimization Approach for Solving Metal Recovery Processing Problem
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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.
KeywordsDC programming Quadratic programming Inequality constraints Manufacturing processes Linearized problem Local search Global search
This work supported by the project “ P2019-3751” of National University of Mongolia.
- 6.Fedorov, V.V.: Theory of Optimal Experiments. Academic Press, New-York (1972)Google Scholar
- 8.Gruzdeva, T., Strekalovsky, A.: An approach to fractional programming via D.C. constraints problem: local search. In: Kochetov, Y., Khachay, M., Beresnev, V., Nurminski, E., Pardalos, P. (eds.) DOOR 2016. LNCS, vol. 9869, pp. 404–417. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-44914-2_32CrossRefGoogle Scholar
- 18.Strekalovsky, A.S.: Elements of Nonconvex Optimization. Nauka, Novosibirsk (2003). (in Russian)Google Scholar
- 20.Strekalovsky, A.S., Yakovleva, T.V.: On a local and global search involved in nonconvex optimization problems. Autom. Remote Control. 65, 375–387 (2004). https://doi.org/10.1023/B:AURC.0000019368.45522.7aMathSciNetCrossRefzbMATHGoogle Scholar