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7 - Primal Heuristics for Mixed-Integer Nonlinear Programming

Published online by Cambridge University Press:  04 April 2025

Timo Berthold ,
Andrea Lodi  and
Domenico Salvagnin
Timo Berthold
Affiliation:
FICO
Andrea Lodi
Affiliation:
Cornell Tech
Domenico Salvagnin
Affiliation:
Università degli Studi di Padova, Italy
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Summary

This chapter discusses the extension of many primal heuristics developed for MIP to mixed integer nonlinear programming, a larger and even more challenging class of mathematical optimization problems that contains MIP. The importance of primal heuristics for this area is highlighted and some novel ideas originated from specifically considering mixed integer nonlinear programs are also reviewed.

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Primal Heuristics in Integer Programming , pp. 92 - 102
Publisher: Cambridge University Press
Print publication year: 2025

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