Symmetry breaking for generalized disjunctive programming formulation of the strip packing problem

Francisco Trespalacios and Ignacio E. Grossmann ()
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Francisco Trespalacios: Carnegie Mellon University
Ignacio E. Grossmann: Carnegie Mellon University

Annals of Operations Research, 2017, vol. 258, issue 2, No 24, 747-759

Abstract: Abstract In this work we present a new generalized disjunctive programming (GDP) formulation for the strip packing problem. The new formulation helps to break some of the symmetry that arises in this problem. The new formulation is further improved for the case in which the heights and lengths of the rectangles are integer numbers. The GDP model can be formulated and solved as a mixed-integer linear programming (MILP) model, using different GDP-to-MILP reformulations. The results show that the MILP reformulations of the new GDP model (and its improvement for rectangles with integer heights and widths) can be solved faster than the previously proposed GDP formulation.

Keywords: Strip packing; Disjunctive programming; Mixed-integer programming (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/s10479-016-2112-9

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