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A generalized Weiszfeld method for the multi-facility location problem
An iterative method is proposed for the K facilities location problem. The problem is relaxed using probabilistic assignments, depending on the distances to the facilities. The probabilities, thatExpand
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Comparison of missing value imputation methods in time series: the case of Turkish meteorological data
This study aims to compare several imputation methods to complete the missing values of spatio–temporal meteorological time series. To this end, six imputation methods are assessed with respect toExpand
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Probabilistic D-Clustering
We present a new iterative method for probabilistic clustering of data. Given clusters, their centers and the distances of data points from these centers, the probability of cluster membership at anyExpand
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Clustering-Based Methodology for Determining Optimal Roadway Configuration of Detectors for Travel Time Estimation
The problem of finding the optimal roadway segment configuration for road-based surveillance technologies to estimate route travel times accurately is addressed. This problem is inherently a spaceExpand
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Clustering current climate regions of Turkey by using a multivariate statistical method
In this study, the hierarchical clustering technique, called Ward method, was applied for grouping common features of air temperature series, precipitation total and relative humidity series of 244Expand
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A genetic algorithm for the uncapacitated single allocation planar hub location problem
Given a set of n interacting points in a network, the hub location problem determines location of the hubs (transfer points) and assigns spokes (origin and destination points) to hubs so as toExpand
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Probabilistic Distance Clustering
Probabilistic distance clustering is an iterative method for probabilistic clustering of data. Given clusters, their centers, and the distances of data points from these centers, the probability ofExpand
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Probabilistic distance clustering adjusted for cluster size
The probabilistic distance clustering method of works well if the cluster sizes are approximately equal. We modify that method to deal with clusters of arbitrary size and for problems where theExpand
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Probabilistic programming models for traffic incident management operations planning
This paper proposes mathematical programming models with probabilistic constraints in order to address incident response and resource allocation problems for the planning of traffic incidentExpand
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The planar hub location problem: a probabilistic clustering approach
  • C. Iyigun
  • Mathematics, Computer Science
  • Ann. Oper. Res.
  • 1 June 2013
Given the demand between each origin-destination pair on a network, the planar hub location problem is to locate the multiple hubs anywhere on the plane and to assign the traffic to them so as toExpand
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