Refined proximity and sensitivity results in linearly constrained convex separable integer programming

DOI10.1016/0024-3795(95)00172-NzbMath0838.90083WikidataQ114852061 ScholiaQ114852061MaRDI QIDQ1899421

Ross Baldick

Publication date: 9 October 1995

Published in: Linear Algebra and its Applications (Search for Journal in Brave)

zbMATH Keywords

sensitivityproximityinteger nonlinear programminglinearly constrained convex separable programmingmeasure of the structure of a linear constraint matrix

Mathematics Subject Classification ID

Integer programming (90C10) Nonlinear programming (90C30) Sensitivity, stability, parametric optimization (90C31)

Related Items (5)

A unified approach to polynomially solvable cases of integer ``non-separable quadratic optimization ⋮ Sensitivity Analysis for Convex Separable Optimization Over Integral Polymatroids ⋮ On the relationship between the integer and continuous solutions of convex programs ⋮ Distances between optimal solutions of mixed-integer programs ⋮ Inverse optimization for linearly constrained convex separable programming problems

Cites Work

• Some proximity and sensitivity results in quadratic integer programming
• The Boolean quadratic polytope: Some characteristics, facets and relatives
• The relationship between integer and real solutions of constrained convex programming
• A unified approach to polynomially solvable cases of integer ``non-separable quadratic optimization
• A Strongly Polynomial Algorithm to Solve Combinatorial Linear Programs
• Degree-two Inequalities, Clique Facets, and Biperfect Graphs
• Sensitivity theorems in integer linear programming
• Convex separable optimization is not much harder than linear optimization
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