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The static stability of support factor‐based rectangular packings: an assessment by regression analysis
Author(s) -
Junqueira Leonardo,
Queiroz Thiago Alves de
Publication year - 2022
Publication title -
international transactions in operational research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.032
H-Index - 52
eISSN - 1475-3995
pISSN - 0969-6016
DOI - 10.1111/itor.12750
Subject(s) - stability (learning theory) , grid , computer science , integer programming , mathematical optimization , factor (programming language) , linear programming , packing problems , outcome (game theory) , longitudinal static stability , integer (computer science) , base (topology) , mathematics , machine learning , engineering , geometry , programming language , mathematical analysis , mathematical economics , aerodynamics , aerospace engineering
This work presents new insights about how solutions of support factor‐based rectangular packings behave in relation to their static stability. In particular, we address the constrained two‐dimensional packing problem, for the solution of which is used a known integer linear programming model that positions items over a grid of points. The model has embedded constraints based on a support factor parameter that ensure a minimum support for the base of items. The solutions obtained from the model are then evaluated by a procedure that verifies the conditions for the static stability. Computational tests were performed on a large variety of randomly generated instances, and the outputs were assessed by means of regression analysis (linear and logistic). The results show which characteristics of the instances contribute directly and inversely to the probability of obtaining statically stable packing patterns. This outcome may be useful to guide the choice of support factor values in some practical contexts.