An algorithmic framework based on primitive directions and nonmonotone line searches for black-box optimization problems with integer variables

  • In this paper, we develop a new algorithmic framework to solve black-box problems with integer variables. The strategy included in the framework makes use of specific search directions (so called primitive directions) and a suitably developed nonmonotone line search, thus guaranteeing a high level of freedom when exploring the integer lattice. First, we describe and analyze a version of the algorithm that tackles problems with only bound constraints on the variables. Then, we combine it with a penalty approach in order to solve problems with simulation constraints. In both cases we prove finite convergence to a suitably defined local minimum of the problem. We report extensive numerical experiments based on a test bed of both bound-constrained and generally-constrained problems. We show the effectiveness of the method when compared to other state-of-the-art solvers for black-box integer optimization.

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Metadaten
Author:Giampaolo Liuzzi, Stefano Lucidi, Francesco Rinaldi
DOI:https://doi.org/10.1007/s12532-020-00182-7
ISSN:1867-2949
Parent Title (English):Mathematical Programming Computation
Publisher:Springer Science and Business Media LLC
Document Type:Article
Language:English
Year of Completion:2020
Tag:Software; Theoretical Computer Science
Volume:12
Issue:4
Page Number:30
First Page:673
Last Page:702
Mathematical Programming Computation :MPC 2020 - Issue 4
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