Abstract
A generic structure found in many distribution, routing, and location applications is
where the decision variables have been partitioned into two sets of variables x ∈ ℜ{sun1} and y ∈ ℜ{sun2}. In particular, assume that the A matrix has very special structure so the problem in the x variables only, is a relatively “easy” problem. For example, if the y variables are fixed at y = y, Ax ≥ b — By might be the constraint set for a transportation problem. See model (TLP) in Subsection 1.3.5 of Chapter 1. The constraint set y ∈ Y, might be a polyhedron, but it could also be a set with discrete variables, or a set with nonlinearities.
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© 1999 Springer Science+Business Media New York
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Martin, R.K. (1999). Projection: Benders’ Decomposition. In: Large Scale Linear and Integer Optimization: A Unified Approach. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-4975-8_10
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DOI: https://doi.org/10.1007/978-1-4615-4975-8_10
Publisher Name: Springer, Boston, MA
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