Wyniki wyszukiwania - BazTech

1

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.

2

Identifying priority areas for the conservation of ecosystem services using GIS-based multicriteria evaluation

Liu Y., Zhang H., Yang X., Wang Y., Wang X., Cai Y.

Polish Journal of Ecology

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2013

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Vol. 61, nr 3

415--430

EN

The rapid global urban growth poses a great risk to the ecosystem services which are vital to sustaining and fulfilling human life. As an essential part of Fuzhou eco-planning task in south-eastern China, we identified the priority conservation areas for ecosystem services to allow a sustainable urban expansion. We modeled and mapped five ecosystem services (carbon storage, timber production, water yield, water-quality improvement and sediment retention) using InVEST and proposed a definition of priority areas for the conservation of ecosystem services. Priority areas for individual ecosystem services showed that 24% of the region was needed to produce 26% of water yield. Between 6 and 17% of the region was required to conserve at least 20% of other four services, depending on the ecosystem service of interest. In addition, scenarios for multiple ecosystem services conservation were developed using the ordered weighted averaging (OWA) method, a multicriteria evaluation method, to take the tradeoffs among ecosystem services into account. The results showed that, along with the decrease of the OWA risk, the overall areas and the areas at both of the conservative levels dropped gradually. Furthermore, two efficiency indices were created to evaluate the performance of different OWA scenarios. Study results suggested that the efficiency of scenarios was associated with the conservation threshold and OWA risk, as well as the spatial correlation among ecosystem services. In sum, identifying priority areas for ecosystem services in a spatially explicit manner, and analyzing tradeoffs between them, can help make land use and natural resource decisions more effective and efficient.

3

Generalized ordered linear regression with regularization

Łęski J., Henzel N.

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2012

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Vol. 60, nr 3

481-489

EN

Linear regression analysis has become a fundamental tool in experimental sciences. We propose a new method for parameter estimation in linear models. The 'Generalized Ordered Linear Regression with Regularization' (GOLRR) uses various loss functions (including the o-insensitive ones), ordered weighted averaging of the residuals, and regularization. The algorithm consists in solving a sequence of weighted quadratic minimization problems where the weights used for the next iteration depend not only on the values but also on the order of the model residuals obtained for the current iteration. Such regression problem may be transformed into the iterative reweighted least squares scenario. The conjugate gradient algorithm is used to minimize the proposed criterion function. Finally, numerical examples are given to demonstrate the validity of the method proposed.

4

Decision Support under Risk by Optimization of Scenario Importance Weighted OWA Aggregations

Ogryczak W., Śliwiński T.

Journal of Telecommunications and Information Technology

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2009

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nr 3

5-13

EN

The problem of evaluation outcomes under several scenarios to form overall objective functions is of considerable importance in decision support under uncertainty. The fuzzy operator defined as the so-called weighted OWA (WOWA) aggregation offers a well-suited approach to this problem. The WOWA aggregation, similar to the classical ordered weighted averaging (OWA), uses the preferential weights assigned to the ordered values (i.e., to the worst value, the second worst and so on) rather than to the specific criteria. This allows one to model various preferences with respect to the risk. Simultaneously, importance weighting of scenarios can be introduced. In this paper we analyze solution procedures for optimization problems with the WOWA objective functions related to decisions under risk. Linear programming formulations are introduced for optimization of theWOWA objective representing risk averse preferences. Their computational efficiency is demonstrated.