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Title: On MILP Models for the OWA Optimization, Journal of Telecommunications and Information Technology, 2012, nr 2

Creator:

Ogryczak, Włodzimierz ; Olender, Paweł

Date:

2012, nr 2

Resource Type:

artykuł

Description:

The problem of aggregating multiple outcomes to form overall objective functions is of considerable importance in many applications. The ordered weighted averaging (OWA) aggregation uses the weights assigned to the ordered values (i.e., to the largest value, the second largest and so on) rather than to the specific coordinates. It allows to evaluate solutions impartially, when distribution of outcomes is more important than assignments these outcomes to the specific criteria. This applies to systems with multiple independent users or agents, whose objectives correspond to the criteria. The ordering operator causes that the OWA optimization problem is nonlinear. Several MILP models have been developed for the OWA optimization. They are built with different numbers of binary variables and auxiliary constraints. In this paper we analyze and compare computational performances of the different MILP model formulations.

Publisher:

Instytut Łączności - Państwowy Instytut Badawczy, Warszawa

Format:

application/pdf

Resource Identifier:

oai:bc.itl.waw.pl:1225 ; ISSN 1509-4553, on-line: ISSN 1899-8852

DOI:

10.26636/jtit.2012.2.1259

ISSN:

1509-4553

eISSN:

1899-8852

Source:

Journal of Telecommunications and Information Technology

Language:

ang

Rights Management:

Biblioteka Naukowa Instytutu Łączności

Subject and keywords:

mixed integer (linear) programming multiple criteria ordered weighted averaging (OWA) location problem

Object collections:

Last modified:

Aug 29, 2024

In our library since:

Jul 8, 2013

Number of object content hits:

275

All available object's versions:

https://bc.itl.waw.pl/publication/1532

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Edition name Date
Ogryczak, Włodzimierz; Olender, Paweł, On MILP Models for the OWA Optimization, Journal of Telecommunications and Information Technology, 2012, nr 2 Aug 29, 2024

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