Automatic Generation of Optimization Algorithms for Production Lot-Sizing Problems
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- @InProceedings{de-Araujo-Pessoa:2019:CEC,
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author = "L. F. {de Araujo Pessoa} and B. Hellingrath and
F. B. {de Lima Neto}",
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booktitle = "2019 IEEE Congress on Evolutionary Computation (CEC)",
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title = "Automatic Generation of Optimization Algorithms for
Production Lot-Sizing Problems",
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year = "2019",
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pages = "1774--1781",
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month = jun,
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keywords = "genetic algorithms, genetic programming",
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DOI = "doi:10.1109/CEC.2019.8789892",
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abstract = "Successful applications of heuristic-based methods are
able to find high-quality solutions for complex
problems in a feasible time frame. However, they are
usually tailored towards the problem instances under
consideration and any changes in the underlying problem
structure might require a redesign of the algorithm,
which is expensive and very time-consuming. This paper
presents results of an automatic algorithm-generation
approach used to find good-performing optimization
methods for the multi-level capacitated lot-sizing
problem, a relevant and hard combinatorial problem in
production planning. A new template for generating
algorithms is proposed for enabling the generation of
different hybridisations between genetic
algorithm-components and mathematical heuristics.
Several experiments are carried out to evaluate the
ability of the proposed method to generate competitive
algorithms for benchmark instances, under consideration
of different functions set and cutoff times. Results
indicate that the method is able to generate heuristic
algorithms that find high-quality solutions
significantly faster than the compared human-designed
algorithm.",
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notes = "Also known as \cite{8789892}",
- }
Genetic Programming entries for
Luis Filipe de Araujo Pessoa
Bernd Hellingrath
Fernando Buarque de Lima Neto
Citations