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Alternative formulations for the ordered weighted averaging objective

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Alternative formulations for the ordered weighted averaging objective. / Chassein, André; Goerigk, Marc.
In: Information Processing Letters, Vol. 115, No. 6-8, 06.2015, p. 604-608.

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Chassein, A & Goerigk, M 2015, 'Alternative formulations for the ordered weighted averaging objective', Information Processing Letters, vol. 115, no. 6-8, pp. 604-608. https://doi.org/10.1016/j.ipl.2015.02.008

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Vancouver

Chassein A, Goerigk M. Alternative formulations for the ordered weighted averaging objective. Information Processing Letters. 2015 Jun;115(6-8):604-608. Epub 2015 Feb 14. doi: 10.1016/j.ipl.2015.02.008

Author

Chassein, André ; Goerigk, Marc. / Alternative formulations for the ordered weighted averaging objective. In: Information Processing Letters. 2015 ; Vol. 115, No. 6-8. pp. 604-608.

Bibtex

@article{c7310a68723a4556954f88b746352211,
title = "Alternative formulations for the ordered weighted averaging objective",
abstract = "The ordered weighted averaging (OWA) objective is an aggregate function over multiple optimization criteria that has received increasing attention by the research community over the last decade. Different to the weighted sum, where a certain weight is assigned to every objective function, weights are attached to ordered objective functions (i.e., for a fixed solution, objective functions are sorted with respect to their size, and weights are assigned to positions within this ordering). As this contains max-min or worst-case optimization as a special case, OWA can also be considered as an alternative approach to robust optimization. For linear programs with OWA objective, compact and extended reformulations exist. We present new such reformulation models with reduced size. A computational comparison indicates that these formulations improve solution times.",
keywords = "Combinatorial problems, Linear programming, Multi-criteria optimization, Ordered weighted averaging",
author = "Andr{\'e} Chassein and Marc Goerigk",
year = "2015",
month = jun,
doi = "10.1016/j.ipl.2015.02.008",
language = "English",
volume = "115",
pages = "604--608",
journal = "Information Processing Letters",
issn = "0020-0190",
publisher = "Elsevier",
number = "6-8",

}

RIS

TY - JOUR

T1 - Alternative formulations for the ordered weighted averaging objective

AU - Chassein, André

AU - Goerigk, Marc

PY - 2015/6

Y1 - 2015/6

N2 - The ordered weighted averaging (OWA) objective is an aggregate function over multiple optimization criteria that has received increasing attention by the research community over the last decade. Different to the weighted sum, where a certain weight is assigned to every objective function, weights are attached to ordered objective functions (i.e., for a fixed solution, objective functions are sorted with respect to their size, and weights are assigned to positions within this ordering). As this contains max-min or worst-case optimization as a special case, OWA can also be considered as an alternative approach to robust optimization. For linear programs with OWA objective, compact and extended reformulations exist. We present new such reformulation models with reduced size. A computational comparison indicates that these formulations improve solution times.

AB - The ordered weighted averaging (OWA) objective is an aggregate function over multiple optimization criteria that has received increasing attention by the research community over the last decade. Different to the weighted sum, where a certain weight is assigned to every objective function, weights are attached to ordered objective functions (i.e., for a fixed solution, objective functions are sorted with respect to their size, and weights are assigned to positions within this ordering). As this contains max-min or worst-case optimization as a special case, OWA can also be considered as an alternative approach to robust optimization. For linear programs with OWA objective, compact and extended reformulations exist. We present new such reformulation models with reduced size. A computational comparison indicates that these formulations improve solution times.

KW - Combinatorial problems

KW - Linear programming

KW - Multi-criteria optimization

KW - Ordered weighted averaging

U2 - 10.1016/j.ipl.2015.02.008

DO - 10.1016/j.ipl.2015.02.008

M3 - Journal article

AN - SCOPUS:84939943447

VL - 115

SP - 604

EP - 608

JO - Information Processing Letters

JF - Information Processing Letters

SN - 0020-0190

IS - 6-8

ER -