A computational analysis of lower bounds for big bucket production planning problems

Kerem Akartunali, Andrew J. Miller

Research output: Contribution to journalArticle

14 Citations (Scopus)

Abstract

In this paper, we analyze a variety of approaches to obtain lower bounds for multi-level production planning problems with big bucket capacities, i.e., problems in which multiple items compete for the same resources. We give an extensive survey of both known and new methods, and also establish relationships between some of these methods that, to our knowledge, have not been presented before. As will be highlighted, understanding the substructures of difficult problems provide crucial insights on why these problems are hard to solve, and this is addressed by a thorough analysis in the paper. We conclude with computational results on a variety of widely used test sets, and a discussion of future research.
LanguageEnglish
Pages729-753
Number of pages25
JournalComputational Optimization and Applications
Volume53
Issue number3
Early online date9 Feb 2012
DOIs
Publication statusPublished - Dec 2012

Fingerprint

Production Planning
Computational Analysis
Lower bound
Planning
Test Set
Substructure
Computational Results
Resources

Keywords

  • production planning
  • lot-sizing
  • integer programming
  • strong formulations
  • Lagrangian relaxation

Cite this

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A computational analysis of lower bounds for big bucket production planning problems. / Akartunali, Kerem; Miller, Andrew J.

In: Computational Optimization and Applications, Vol. 53, No. 3, 12.2012, p. 729-753.

Research output: Contribution to journalArticle

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