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A Branch-and-Bound Algorithm for Multiobjective Mixed-integer Convex OptimizationOutlook and further possible improvements

A Branch-and-Bound Algorithm for Multiobjective Mixed-integer Convex Optimization: Outlook and... [In this Chapter, we discuss an extension of the proposed algorithm to the nonconvex case. Therefore, we introduce the concept of convex underestimators. As we have seen in Example 2.13, the assumption of convexity of f and g for (MOMICP) in Assumption 2.9 can be very restricting.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

A Branch-and-Bound Algorithm for Multiobjective Mixed-integer Convex OptimizationOutlook and further possible improvements

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Publisher
Springer Fachmedien Wiesbaden
Copyright
© Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2020
ISBN
978-3-658-29148-8
Pages
61 –62
DOI
10.1007/978-3-658-29149-5_6
Publisher site
See Chapter on Publisher Site

Abstract

[In this Chapter, we discuss an extension of the proposed algorithm to the nonconvex case. Therefore, we introduce the concept of convex underestimators. As we have seen in Example 2.13, the assumption of convexity of f and g for (MOMICP) in Assumption 2.9 can be very restricting.]

Published: Jan 22, 2020

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