Newton's Method for Multiobjective Optimization

By M. Drummond, Jörg Fliege, Rolando Gárciga Otero, Benar Fux Svaiter. SIAM Journal on Optimization, 2009

429 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Management Science and Operations Research, Numerical Analysis

View Paper: https://www.semanticscholar.org/paper/65ad5f4aad2d717cadedfb32f505a2e0ae5b61fb

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Theory and Mathematics

1. Adanay Martín
2. Abid Ali Khan
3. Oliver Schütze
4. Joydeep Dutta
5. Imran Ali Chaudhry
6. Y. Kaya
7. Yunier Bello Cruz

In Management Science and Operations Research

1. Abid Ali Khan
2. Oliver Schütze
3. Joydeep Dutta
4. Imran Ali Chaudhry
5. Y. Kaya
6. Adanay Martín

In Numerical Analysis

1. Abid Ali Khan
2. Oliver Schütze
3. Joydeep Dutta
4. Imran Ali Chaudhry
5. Y. Kaya
6. Adanay Martín
7. Yunier Bello Cruz

Citations in the corpus

• A research survey: review of flexible job shop scheduling techniques (2016, methodology): “…Minimum of makespan, total flow time, mean tardiness, the number of tardy jobs, and the max tardiness 8 Pérez and Raupp (2014) Research Newton’s method (Fliege et al., 2009) based hierarchical heuristic algorithm Minimum of makespan, workload of most loaded machine, total workload of…”
• Pareto Tracer: a predictor–corrector method for multi-objective optimization problems (2018, methodology): “Further, in Fliege et al. (2009), a variation of the Armijo rule to control the step length t along ν is developed: starting with t= 1, t is decreased (e.g. by half) until the next iteration (x + tν) satisfies F(x + tν) ≤ F(x) + ctδe, (29) where c is a constant (e.g. c= 0.1) and e ∈ Rk is the…”
• A new scalarization and numerical method for constructing the weak Pareto front of multi-objective optimization problems (2011, methodology): “In most of these works, various types of scalarization are considered (notably except in [8,13,14,16,22,25]), and one of the main concerns in these efforts is to get a more-or-less uniform distribution in the value space of the points found by solving the single-objective problem (or scalarization).”
• Convergence of the projected gradient method for quasiconvex multiobjective optimization (2011, background): “Other classical methods for solving scalar optimization problems have been extended for the setting of vector-valued optimization problems (see [11,13,15–18]).”