The Lagrangian Relaxation Method for Solving Integer Programming Problems

( This article originally appeared in Management Science, January 1981, Volume 27, Number 1, pp. 1–18, published by The Institute of Management Sciences. ) One of the most computationally useful ideas of the 1970s is the observation that many hard integer programming problems can be viewed as easy p...

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Vydané v:Management science Ročník 50; číslo Supplement 12; s. 1861 - 1871
Hlavný autor: Fisher, Marshall L
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: INFORMS 01.12.2004
Institute for Operations Research and the Management Sciences
Edícia:Management Science
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ISSN:0025-1909, 1526-5501
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Shrnutí:( This article originally appeared in Management Science, January 1981, Volume 27, Number 1, pp. 1–18, published by The Institute of Management Sciences. ) One of the most computationally useful ideas of the 1970s is the observation that many hard integer programming problems can be viewed as easy problems complicated by a relatively small set of side constraints. Dualizing the side constraints produces a Lagrangian problem that is easy to solve and whose optimal value is a lower bound (for minimization problems) on the optimal value of the original problem. The Lagrangian problem can thus be used in place of a linear programming relaxation to provide bounds in a branch and bound algorithm. This approach has led to dramatically improved algorithms for a number of important problems in the areas of routing, location, scheduling, assignment and set covering. This paper is a review of Lagrangian relaxation based on what has been learned in the last decade.
Bibliografia:ObjectType-Article-2
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ISSN:0025-1909
1526-5501
DOI:10.1287/mnsc.1040.0263