Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/335146 
Year of Publication: 
2025
Citation: 
[Journal:] Optimization Letters [ISSN:] 1862-4480 [Volume:] 19 [Issue:] 9 [Publisher:] Springer [Place:] Berlin, Heidelberg [Year:] 2025 [Pages:] 1883-1904
Publisher: 
Springer, Berlin, Heidelberg
Abstract: 
Bringing together nonlinear optimization with polyhedral and integrality constraints enables versatile modeling, but poses significant computational challenges. We investigate a method to address these problems based on sequential mixed-integer linearization with trust region safeguard, computing feasible iterates via calls to a generic mixed-integer linear solver. Convergence to critical, possibly suboptimal, feasible points is established for arbitrary starting points. Finally, we present numerical applications in nonsmooth optimal control and optimal network design and operation.
Subjects: 
Mixed-integer programming
Nonlinear programming
Successive linearization schemes
Trust region methods
Persistent Identifier of the first edition: 
Creative Commons License: 
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Document Type: 
Article
Document Version: 
Published Version

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