Name
Abstract | ||
|---|---|---|
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 certain 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. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/s00291-016-0453-z | OR Spectrum |
Keywords | Field | DocType |
Multiobjective optimization, Nonconvex optimization, Decomposition, Quadratic scalarization, Weighted-Chebyshev method | Mathematical optimization,Nonlinear system,Quadratic equation,Multi-objective optimization,Business management,Multiobjective optimization problem,Engineering design process,Operations management,Mathematics,Special case | Journal |
Volume | Issue | ISSN |
38 | 4 | 0171-6468 |
Citations | PageRank | References |
0 | 0.34 | 8 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Brian Dandurand | 1 | 9 | 2.18 |
| Margaret M. Wiecek | 2 | 213 | 22.90 |