Ernesto G. Birgin
University of São Paulo
131 Papers
517 Citations
Ernesto G. Birgin is an academic researcher from University of São Paulo. The author has contributed to research in topics: Nonlinear programming & Augmented Lagrangian method. The author has an hindex of 35, co-authored 112 publications. Previous affiliations of Ernesto G. Birgin include State University of Campinas.
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Papers
A note on an L-approach for solving the manufacturer's pallet loading problem
TL;DR: By simply using a different data structure, the runtime is considerably reduced in spite of larger (but affordable) memory requirements, which makes the algorithm much more acceptable for supporting actual decisions in pallet loading.
A filtered beam search method for the m-machine permutation flowshop scheduling problem minimizing the earliness and tardiness penalties and the waiting time of the jobs
TL;DR: This paper addresses the minimization of the absolute deviation of job completion times from a common due date in a flowshop scheduling problem and proposes a filtered beam search method that explores specific characteristics of the considered environment.
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Method of sentinels for packing items within arbitrary convex regions
Ernesto G. Birgin,José Mario Martínez,Walter F. Mascarenhas,Débora P. Ronconi +3 more
- 01 Jun 2006
TL;DR: A new method is introduced for packing items in convex regions of the Euclidian n-dimensional space based on the new concept of sentinels, which becomes a global finite-dimensional continuous optimization problem.
Spectral projected gradient and variable metric methods for optimization with linear inequalities
TL;DR: This paper presents the particular case in which the convex domain is a polytope described by a finite set of linear inequalities is considered, and a dual approach is adopted, by means of which subproblems become convex quadratic minimization problems with box constraints.
Metaheuristics for the online printing shop scheduling problem
TL;DR: Numerical experiments with classical instances of the flexible job shop scheduling problem show that the introduced methods are also competitive when applied to this particular case and that they outperform a half-heuristic-half-exact off-the-shelf solver by a large extent.
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