### Abstract

Several problems in operations research, such as the assembly line crew scheduling problem and the k-partitioning problem can be cast as the problem of finding the intra-column rearrangement (permutation) of a matrix such that the row sums show minimum variability. A necessary condition for optimality of the rearranged matrix is that for every block containing one or more columns it must hold that its row sums are oppositely ordered to the row sums of the remaining columns. We propose the block rearrangement algorithm with variance equalization (BRAVE) as a suitable method to achieve this situation. It uses a carefully motivated heuristic—based on an idea of variance equalization—to find optimal blocks of columns and rearranges them. When applied to the number partitioning problem, we show that BRAVE outperforms the well-known greedy algorithm and the Karmarkar–Karp differencing algorithm.

Language | English |
---|---|

Pages | 31–50 |

Number of pages | 20 |

Journal | 4OR |

Volume | 16 |

DOIs | |

State | Published - 2018 |

### Cite this

*4OR*,

*16*, 31–50. DOI: 10.1007/s10288-017-0344-4

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*4OR*, vol 16, pp. 31–50. DOI: 10.1007/s10288-017-0344-4

**Block rearranging elements within matrix columns to minimize the variability of the row sums.** / Boudt, K.M.R.; Jakobsons, Edgars; Vanduffel, Steven.

Research output: Contribution to journal › Article

TY - JOUR

T1 - Block rearranging elements within matrix columns to minimize the variability of the row sums

AU - Boudt,K.M.R.

AU - Jakobsons,Edgars

AU - Vanduffel,Steven

PY - 2018

Y1 - 2018

N2 - Several problems in operations research, such as the assembly line crew scheduling problem and the k-partitioning problem can be cast as the problem of finding the intra-column rearrangement (permutation) of a matrix such that the row sums show minimum variability. A necessary condition for optimality of the rearranged matrix is that for every block containing one or more columns it must hold that its row sums are oppositely ordered to the row sums of the remaining columns. We propose the block rearrangement algorithm with variance equalization (BRAVE) as a suitable method to achieve this situation. It uses a carefully motivated heuristic—based on an idea of variance equalization—to find optimal blocks of columns and rearranges them. When applied to the number partitioning problem, we show that BRAVE outperforms the well-known greedy algorithm and the Karmarkar–Karp differencing algorithm.

AB - Several problems in operations research, such as the assembly line crew scheduling problem and the k-partitioning problem can be cast as the problem of finding the intra-column rearrangement (permutation) of a matrix such that the row sums show minimum variability. A necessary condition for optimality of the rearranged matrix is that for every block containing one or more columns it must hold that its row sums are oppositely ordered to the row sums of the remaining columns. We propose the block rearrangement algorithm with variance equalization (BRAVE) as a suitable method to achieve this situation. It uses a carefully motivated heuristic—based on an idea of variance equalization—to find optimal blocks of columns and rearranges them. When applied to the number partitioning problem, we show that BRAVE outperforms the well-known greedy algorithm and the Karmarkar–Karp differencing algorithm.

KW - Assembly line crew scheduling

KW - Greedy algorithm

KW - k-Partitioning

KW - Karmarkar–Karp differencing algorithm

KW - Rearrangements

UR - http://www.scopus.com/inward/record.url?scp=85014069693&partnerID=8YFLogxK

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U2 - 10.1007/s10288-017-0344-4

DO - 10.1007/s10288-017-0344-4

M3 - Article

VL - 16

SP - 31

EP - 50

JO - 4OR

T2 - 4OR

JF - 4OR

SN - 1619-4500

ER -