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A branch-and-cut and a parallel algorithm for packing two-dimensional rectangles in a circular container
Silva, Allyson; Coelho, Leandro C.; Darvish, Maryam; … - 2021
Persistent link: https://www.econbiz.de/10012615643
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Linear programming for a cutting problem in the wood processing industry : a case study
Koch, Sören; König, Sebastian; Wäscher, Gerhard - 2008
Persistent link: https://www.econbiz.de/10003727779
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The two-dimensional cutting stock problem within the roller blind production process
Gelder, E.R. de (contributor);  … - 2007
Persistent link: https://www.econbiz.de/10003754027
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Optimally loading clocked tow trains for JIT-supply of mixed-model assembly lines
Emde, Simon; Fliedner, Malte; Boysen, Nils - 2009
Persistent link: https://www.econbiz.de/10003928142
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A reduction approach for solving the rectangle packing area minimization problem
Bortfeldt, Andreas - 2011
Persistent link: https://www.econbiz.de/10009428192
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Ein verteilt-paralleler genetischer Algorithmus für Containerbeladeprobleme
Gehring, Hermann - 1999
Persistent link: https://www.econbiz.de/10013409130
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Packing problems and project scheduling models : an integrated perspective
Hartmann, Sönke - 1999
This paper considers two problem classes that are important to researchers as well as practitioners, namely packing and … project scheduling problems. First, the two problem categories are described. This includes a classification of packing … application, similarities of their mathematical structures are examined. It is shown that all packing problems considered here are …
Persistent link: https://www.econbiz.de/10011734909
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On the origin of r-concavity and related concepts
Balogh, Tamás L.; Ewerhart, Christian - 2015
In a less widely known contribution, Béla Martos (1966, Hungarian Academy of Sciences) introduced a generalized notion of concavity that is closely related to what is nowadays known as r-concavity in the operations research literature, and that is identical to what is nowadays known as...
Persistent link: https://www.econbiz.de/10010486881
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DCISolver.jl: a Julia solver for nonlinear optimization using dynamic control of infeasibility
Migot, Tangi; Orban, Dominique; Siqueira, Abel S. - 2021
Persistent link: https://www.econbiz.de/10012704517
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FluxNLPModels.jl and KnetNLPModels.jl : connecting deep learning models with optimization solvers
Rahbarnia, Farhad; Raynaud, Paul - 2023
Persistent link: https://www.econbiz.de/10014312825