Abstract
The paper presents strategies optimization for an existing automated warehouse located in a steelmaking industry. Genetic algorithms are applied to this purpose and three different popular algorithms capable to deal with multi-objective optimization are compared. The three algorithms, namely the Niched Pareto Genetic Algorithm, the Non-dominated Sorting Genetic Algorithm 2 and the Strength Pareto Genetic Algorithm 2, are described in details and the achieved results are widely discussed; moreover several statistical tests have been applied in order to evaluate the statistical significance of the obtained results.
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The authors wish to gratefully acknowledge ILVA Racconigi Works for providing data and relevant information and for the fruitful discussions, which significantly contributed to the present analysis.
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Nastasi, G., Colla, V., Cateni, S. et al. Implementation and comparison of algorithms for multi-objective optimization based on genetic algorithms applied to the management of an automated warehouse. J Intell Manuf 29, 1545–1557 (2018). https://doi.org/10.1007/s10845-016-1198-x
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DOI: https://doi.org/10.1007/s10845-016-1198-x