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Hybrid Models for the OWA Optimization

Olender P.

Journal of Telecommunications and Information Technology

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2016

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nr 4

22--30

EN

When dealing with multicriteria problems, the aggregation of multiple outcomes plays an essential role in finding a solution, as it reflects the decision-maker's preference relation. The Ordered Weighted Averaging (OWA) operator provides a exible preference model that generalizes many objective functions. It also ensures the impartiality and allow to obtain equitable solutions, which is vital when the criteria represent evaluations of independent individuals. These features make the OWA operator very useful in many fields, one of which is location analysis. However, in general the OWA aggregation makes the problem nonlinear and hinder its computational complexity. Therefore, problems with the OWA operator need to be devised in an efficient way. The paper introduces new general formulations for OWA optimization and proposes for them some simple valid inequalities to improve efficiency. A hybrid structure of proposed models makes the number of binary variables problem type dependent and may reduce it signicantly. Computational results show that for certain problem types, some of which are very useful in practical applications, the hybrid models perform much better than previous general models from literature.

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Comparison of Selected Fair-optimization Methods for Flow Maximization between Given Pairs of Nodes in Telecommunications Network

Zalewski G., Ogryczak W.

Journal of Telecommunications and Information Technology

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2016

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nr 3

18--24

EN

Dimensioning of telecommunications networks requires the allocation of the ows (bandwidth) to given trac demands for the source-destination pairs of nodes. Unit ow allocated to the given demand is associated with revenue that may vary for dierent demands. Problem the decision-making basic algorithms to maximize the total revenue may lead to the solutions that are unacceptable, due to "starvation" or "locking" of some demand paths less attractive with respect to the total revenue. Therefore, the fair optimization approaches must be applied. In this paper, two fair optimization methods are analyzed: the method of ordered weighted average (OWA) and the reference point method (RPM). The study assumes that ows can be bifurcated thus realized in multiple path schemes. To implement optimization model the AMPL was used with general-purpose linear programming solvers. As an example of the data, the Polish backbone network was used.

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An heuristic approach for mapping landslide hazard by integrating fuzzy logic with analytic hierarchy process

Gorsevski P. V., Jankowski P., Gessler P. E.

Control and Cybernetics

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2006

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Vol. 35, no 1

121-146

EN

This study presents an integration of fuzzy sets theory with analytic hierarchy process (AHP) to model landslide hazard. The approach involves developing expert knowledge from existing landslide datascts which arc used for standardizing digital terrain attributes, a pairwise comparison method for the elicitation of attribute weights, and their subsequent aggregation through weighted linear combination (WLC) and ordered weighted average fOWA) function to generate landslide hazard maps. The approach enhances tlic methodology for modeling landslide hazard in roaded and roadless areas through the derivation of probabilistic maps. The maps can be used as a decision support tool in forest management and planning. A case study from the Clearwater National Forest in central Idaho, USA, illustrates the application of the approach in a practical setting.