Toward Global Search for Local Optima

Jens Deussen (), Jonathan Hüser and Uwe Naumann
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Jens Deussen: RWTH Aachen University
Jonathan Hüser: RWTH Aachen University
Uwe Naumann: RWTH Aachen University

A chapter in Operations Research Proceedings 2019, 2020, pp 97-104 from Springer

Abstract: Abstract First steps toward a novel deterministic algorithm for finding a minimum among all local minima of a nonconvex objective over a given domain are discussed. Nonsmooth convex relaxations of the objective and of its gradient are optimized in the context of a global branch and bound method. While preliminary numerical results look promising further effort is required to fully integrate the method into a robust and computationally efficient software solution.

Keywords: Nonconvex optimization; McCormick relaxation; Piecewise linearization (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:spr:oprchp:978-3-030-48439-2_12

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DOI: 10.1007/978-3-030-48439-2_12

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