Theory of Linear and Integer Programming¶
Schrijver, A. (1998). Theory of Linear and Integer Programming. Wiley.
Cited by¶
5 citations across 5 artifacts.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Branch and Bound
- The alternate-origin assignments to computer_science_software_engineering (for the algorithmic and implementation depth) and mathematics (for the relaxation-and-bounding theoretical foundations per Schrijver's (1986)
This sourcefoundational mathematical reference for the polyhedral-combinatorics and relaxation-and-bounding mathematics underlying branch-and-cut.
Supported in partVerified against the work's full text
The Wiley page shows Schrijver (1986) is a mathematical treatment of linear/integer programming and combinatorial optimization aimed at mathematics and CS readers; it never mentions relaxation or bounding.
“A special feature is the author's coverage of important recent developments in linear and integer programming. Applications to combinatorial optimization are given, and the author also includes extensive historical surveys and bibliographies. The book is intended for graduate students and researchers in operations research, mathematics and computer science.”
- The alternate-origin assignments to computer_science_software_engineering (for the algorithmic and implementation depth) and mathematics (for the relaxation-and-bounding theoretical foundations per Schrijver's (1986)
- Integer Linear Programming (ILP)
- In combinatorial optimization, ILP provides a unifying framework within which many problem classes (matching, covering, packing, routing, scheduling, assignment) can be expressed and solved, as Schrijver's (1986) comprehensive treatment of linear and integer programming makes explicit.
This sourceFoundational mathematical reference for linear and integer programming theory; rigorous treatment of polyhedral combinatorics and the relaxation-and-bounding mathematics underlying branch-and-cut.
Supported in partVerified against the work's full text
The page we hold is Wiley's description of the book, which confirms it covers the theory and algorithms of linear and integer programming but names no combinatorial-optimization problem classes and no 'unifying framework'.
“This book describes the theory of linear and integer programming and surveys the algorithms for linear and integer programming problems, focusing on complexity analysis.”
- In combinatorial optimization, ILP provides a unifying framework within which many problem classes (matching, covering, packing, routing, scheduling, assignment) can be expressed and solved, as Schrijver's (1986) comprehensive treatment of linear and integer programming makes explicit.
- Linear Programming (LP)
- Linear programming manages complexity through mathematical structure and algorithmic efficiency, the polyhedral and algorithmic theory of which Schrijver (1986) treats comprehensively.
This sourceFoundational mathematical reference for linear and integer programming theory; rigorous treatment of polyhedral combinatorics and the relaxation-and-bounding mathematics underlying branch-and-cut.
Supported in partVerified against the publisher's abstract
The publisher's description confirms Schrijver's book describes LP/IP theory and surveys its algorithms with attention to complexity; it never says 'polyhedral' or 'comprehensive'.
“This book describes the theory of linear and integer programming and surveys the algorithms for linear and integer programming problems, focusing on complexity analysis.”
- Linear programming manages complexity through mathematical structure and algorithmic efficiency, the polyhedral and algorithmic theory of which Schrijver (1986) treats comprehensively.
Domain-specific¶
- Balanced matrix
- Fourier–Motzkin Elimination
- Standard treatments connect this algebraic rule to polyhedral projection and quantifier elimination for linear real arithmetic.
This sourceProvides standard polyhedral and linear-inequality treatment of projection, elimination, and feasibility.
- Standard treatments connect this algebraic rule to polyhedral projection and quantifier elimination for linear real arithmetic.
Verification¶
Does it exist? Not checked yet. This entry carries no identifier to resolve. It was extracted from the citation as written in the article, normalized, and deduplicated against the rest of the registry.
Does it back the claim? Read against the text for 3 of 5 citations: 3 supported in part. Each verdict is shown under its citation below, with what in the work backs the sentence.
Support is checked per citation rather than per work — the same source can be cited soundly in one article and wrongly in another. Per-citation recording began recently, so a citation with no recorded check is a gap in the record rather than evidence it went unchecked.
See how references were verified.
Links previously used in the corpus¶
Before the registry existed this work was also linked 1 other way.
Registry ID ref:fc14e2b725b9 · see in the full table