The Two-Dimensional Strip Packing Problem: What Matters?
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.
KeywordsStrip packing problems Cutting and packing problems Principal component analysis Knowledge discovery
The second author was supported by FCT – Fundação para a Ciência e a Tecnologia within the grant SFRH/BPD/98981/2013. The research was partially supported by ERDF European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation - COMPETE 2020 Programme within project “POCI-01-0145-FEDER-006961”, and by National Funds through the Portuguese funding agency, FCT – Fundação para a Ciência e a Tecnologia as part of project “UID/EEA/50014/2013”.
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