Quadratic scalarization for decomposed multiobjective optimization

Event Sponsor: 
Mathmatics and Computer Science Division Seminar - LANS
Start Date: 
May 8 2019 - 10:30am
Building 240/Room 1404-1405
Argonne National Laboratory
Brian Dandurand
Speaker(s) Title: 
Postdoctoral Appointee, MCS

Practical applications in multidisciplinary engineering design, business management, and military planning require distributed solution approaches for solving nonconvex, multiobjective optimization problems (MOPs). Under this motivation, a quadratic scalarization method (QSM) is developed with the goal to preserve decomposable structures of the MOP while addressing nonconvexity in a manner that avoids a high degree of nonlinearity and the introduction of additional nonsmoothness.

Under mild assumptions, necessary and sufficient conditions for QSM-generated solutions to be weakly and properly efficient for an MOP are developed, with any form of efficiency being understood in a local sense. QSM is shown to correspond with the relaxed, reformulated weighted-Chebyshev method as a special case. An example is provided for demonstrating the application of QSM to a nonconvex MOP.

Miscellaneous Information: 

This seminar will be streamed. https://anlpress.cels.anl.gov/cels-seminars/.

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