The two-dimensional strip packing problem: What matters? Alvaro Luiz Júnior en José Fernando Oliveira en António Miguel Gomes en Elsa Marília Silva en
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dc.contributor.other 265 en
dc.contributor.other 1249 en 2020-06-30T08:37:02Z 2020-06-30T08:37:02Z 2018 en
dc.description.abstract This paper presents an exploratory approach to study and identify the main characteristics of the two-dimensional strip packing problem (2D-SPP). A large number of variables was defined to represent the main problem characteristics, aggregated in six groups, established through qualitative knowledge about the context of the problem. Coefficient correlation are used as a quantitative measure to validate the assignment of variables to groups. A principal component analysis (PCA) is used to reduce the dimensions of each group, taking advantage of the relations between variables from the same group. Our analysis indicates that the problem can be reduced to 19 characteristics, retaining most part of the total variance. These characteristics can be used to fit regression models to estimate the strip height necessary to position all items inside the strip. © Springer International Publishing AG 2018. en
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dc.language eng en
dc.rights info:eu-repo/semantics/openAccess en
dc.title The two-dimensional strip packing problem: What matters? en
dc.type Publication en
dc.type conferenceObject en
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