Titlebook: Computational Combinatorial Optimization; Optimal or Provably Michael Jünger,Denis Naddef Textbook 2001 Springer-Verlag Berlin Heidelberg

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Branch, Cut, and Price: Sequential and Parallel,s and variables can be generated dynamically throughout the search tree. The ability to handle constantly changing sets of cuts and variables allows these algorithms to undertake the solution of very large-scale DOPs; however, it also leads to interesting implementational challenges. These lecture n

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TSP Cuts Which Do Not Conform to the Template Paradigm, used subtour inequalities as well as cutting planes of Gomory‘s type. The practice of looking for and using cuts that match prescribed templates in conjunction with Gomory cuts was continued in computer codes of Miliotis, Land, and Fleischmann. Gr?tschel, Padberg, and Hong advocated a different pol

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Projection and Lifting in Combinatorial Optimization,r partial relaxations. It discusses the compact representation of the convex hull of a union of polyhedra through extended formulation, the connection between the projection of the latter and the polar of the convex hull, as well as the sequential convexification of facial disjunctive programs, amon

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Branch, Cut, and Price: Sequential and Parallel,which we have drawn most of our experience, is a powerful, state-of-the-art library that implements the generic framework of a BCP algorithm. The library’s modular design makes it easy to use in a variety of problem settings and on a variety of hardware platforms. All library subroutines are generic

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https://doi.org/10.1007/978-3-642-99292-6r partial relaxations. It discusses the compact representation of the convex hull of a union of polyhedra through extended formulation, the connection between the projection of the latter and the polar of the convex hull, as well as the sequential convexification of facial disjunctive programs, amon

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https://doi.org/10.1007/978-3-642-99292-6ation. This typically allows one to obtain a linear description of the convex hull of the feasible solutions of the subproblem. Such tight reformulations for the subproblems play an important role in solving the original planning problem to optimality..We then review two important classes of extensi