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Genetic algorithms for inventory constrained scheduling on a single machine
Briskorn, Dirk; Choi, Byung-Cheon; Lee, Kangbok; Leung, … - 2009
Persistent link: https://www.econbiz.de/10003922464
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Genetic algorithms for inventory constrained scheduling on a single machine
Briskorn, Dirk; Choi, Byung-cheon; Lee, Kangbok; Leung, … - 2009
Persistent link: https://www.econbiz.de/10011325639
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Methods
Drexl, Andreas; Salewski, Frank - 1996
Persistent link: https://www.econbiz.de/10011806933
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A comparative genetic algorithm for resource-constraint project scheduling
Hartmann, Sönke - 1997
Persistent link: https://www.econbiz.de/10011787474
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Scheduling medical research experiments : an application of project scheduling methods
Hartmann, Sönke - 1997
Persistent link: https://www.econbiz.de/10011787477
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Genetic algorithms for inventory constrained scheduling on a single machine
Briskorn, Dirk; Choi, Byung-Cheon; Lee, Kangbok; Leung, … - 2009
genetic algorithm framework to tackle them. The focus is on discussion of different representations with respect to redundancy …
Persistent link: https://www.econbiz.de/10011558720
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A general framework for scheduling equipment and manpower on container terminals
Hartmann, Sönke - 2002
a simple dispatching heuristic as well as a more advanced genetic algorithm for the general model. Based on a tailored … results that suggest that the genetic algorithm is well suited for application in practice. …
Persistent link: https://www.econbiz.de/10011725594
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Self-adapting genetic algorithms with an application to project scheduling
Hartmann, Sönke - 1999
. When designing a genetic algorithm, there may be several alternatives for a component such as crossover, mutation or … such cases, we suggest to include alternative components into the genetic algorithm. Indicating the component to be … actually used in the genotype, this allows the genetic algorithm to adapt itself. That is, the genetic algorithm learns which …
Persistent link: https://www.econbiz.de/10011734932
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Self-adapting genetic algorithms with an application to project scheduling
Hartmann, Sönke - 1999
. When designing a genetic algorithm, there may be several alternatives for a component such as crossover, mutation or … such cases, we suggest to include alternative components into the genetic algorithm. Indicating the component to be … actually used in the genotype, this allows the genetic algorithm to adapt itself. That is, the genetic algorithm learns which …
Persistent link: https://www.econbiz.de/10011558747
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A general framework for scheduling equipment and manpower on container terminals
Hartmann, Sönke - 2002
a simple dispatching heuristic as well as a more advanced genetic algorithm for the general model. Based on a tailored … results that suggest that the genetic algorithm is well suited for application in practice. …
Persistent link: https://www.econbiz.de/10011558786