A First Course in Combinatorial Optimization by Jon Lee

By Jon Lee

Jon Lee specializes in key mathematical principles resulting in worthy versions and algorithms, instead of on info constructions and implementation info, during this introductory graduate-level textual content for college kids of operations study, arithmetic, and computing device technology. the point of view is polyhedral, and Lee additionally makes use of matroids as a unifying suggestion. subject matters comprise linear and integer programming, polytopes, matroids and matroid optimization, shortest paths, and community flows. difficulties and routines are integrated all through in addition to references for additional examine.

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Y p ) be an optimal solution of D. Let m(k) k k y i ai j , so y k is feasible for Dk . Note that it is not claimed that ckj := i=1 this is a weight splitting of c. However, because (y 1 , y 2 , . . , y p ) is feasible for D, we do have p p ckj = y ik aikj ≥ c j . k=1 k=1 Therefore, we have a natural “weight covering” of c. Applying the Weak Duality Theorem to the pair Pk , Dk gives nj=1 ckj x j ≤ m(k) k k i=1 y i bi . Adding up over k gives the following right-hand inequality, and p the left-hand inequality follows from x ≥ 0 and c ≤ k=1 ck : p n p m(k) n cjx j ≤ ckj x j ≤ j=1 k=1 j=1 y ik bk .

I m a iη j β + η j of nonbasic The reduced cost c η j = c j − cβ Aη j = cη j − i=1 variable xη j will never be identically zero because it always has an η j term. Therefore, the perturbed problem does not suffer from dual degeneracy, and the objective value of the basic solution x ∗ , which is nj=1 c j x ∗j = nj=1 c j x ∗j + n j ∗ x j , decreases at each iteration. Because there are only a finite number j=1 of bases, we have a finite version of the Dual Simplex Method. 8 Totally Unimodular Matrices, Graphs, and Digraphs Some combinatorial-optimization problems can be solved with a straightforward application of linear-programming methods.

Therefore, we really are carrying out valid steps of the Primal Simplex Method with respect to the unperturbed problem P . By filling in all of these details, we have provided a constructive proof of the following result. 4 Sensitivity Analysis Char Count= 0 27 Strong Optimal-Basis Theorem. If P and D are feasible, then there is a basis β that is both primal feasible and dual feasible (hence, optimal). This section closes with a geometric view of the feasible basic solutions visited by the Primal Simplex Method.

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