@article {1535,
	title = {Learning prototypes for multiple instance learning.},
	journal = {Turkish Journal of Electrical Engineering \& Computer Sciences},
	volume = {29},
	year = {2021},
	author = {{\"O}zg{\"u}r Emre Sivrikaya and Mert Y{\"u}kselg{\"o}n{\"u}l and Mustafa Gokce Baydogan}
}
@article {1424,
	title = {A linear programming approach to multiple instance learning},
	journal = {Turkish Journal of Electrical Engineering \& Computer Sciences},
	volume = {29},
	year = {2021},
	pages = {2186{\textendash}2201},
	author = {Emel {\c S}eyma K{\"u}{\c c}{\"u}ka{\c s}c{\i} and Mustafa Gokce Baydogan and Z C Ta{\c s}k{\i}n}
}
@conference {1185,
	title = {Linear-Time Generation of Random Chordal Graphs},
	booktitle = {International Conference on Algorithms and Complexity},
	year = {2017},
	publisher = {Springer},
	organization = {Springer},
	author = {Oylum {\c S}eker and Pinar Heggernes and Ekim, Tinaz and Z. Caner Ta{\c s}k{\i}n}
}
@article {657,
	title = {Learning a symbolic representation for multivariate time series classification},
	journal = {Data Mining and Knowledge Discovery},
	volume = {29},
	year = {2015},
	month = {03/2015},
	pages = {400-422},
	publisher = {Springer US},
	abstract = {<p>Multivariate time series (MTS) classification has gained importance with the increase in the number of temporal datasets in different domains (such as medicine, finance, multimedia, etc.). Similarity-based approaches, such as nearest-neighbor classifiers, are often used for univariate time series, but MTS are characterized not only by individual attributes, but also by their relationships. Here we provide a classifier based on a new symbolic representation for MTS (denoted as SMTS) with several important elements. SMTS considers all attributes of MTS simultaneously, rather than separately, to extract information contained in the relationships. Symbols are learned from a supervised algorithm that does not require pre-defined intervals, nor features. An elementary representation is used that consists of the time index, and the values (and first differences for numerical attributes) of the individual time series as columns. That is, there is essentially no feature extraction (aside from first differences) and the local series values are fused to time position through the time index. The initial representation of raw data is quite simple conceptually and operationally. Still, a tree-based ensemble can detect interactions in the space of the time index and time values and this is exploited to generate a high-dimensional codebook from the terminal nodes of the trees. Because the time index is included as an attribute, each MTS is learned to be segmented by time, or by the value of one of its attributes. The codebook is processed with a second ensemble where now implicit feature selection is exploited to handle the high-dimensional input. The constituent properties produce a distinctly different algorithm. Moreover, MTS with nominal and missing values are handled efficiently with tree learners. Experiments demonstrate the effectiveness of the proposed approach in terms of accuracy and computation times in a large collection multivariate (and univariate) datasets.</p>},
	keywords = {codebook, Decision trees, supervised learning},
	issn = {1384-5810},
	doi = {10.1007/s10618-014-0349-y},
	url = {http://dx.doi.org/10.1007/s10618-014-0349-y},
	author = {Mustafa Gokce Baydogan and Runger, George}
}
@article {1467,
	title = {Locating recycling facilities for IT based electronic waste in Turkey},
	journal = {Journal of Cleaner Production},
	volume = {105},
	year = {2015},
	month = {Oct},
	pages = {324{\textendash}336},
	issn = {09596526},
	author = {Necati Aras and Aybek Korugan and B{\"U}Y{\"U}K{\"O}ZKAN FEYZ{\.I}O{\u G}LU, G{\"U}L{\c C}{\.I}N and S{\.I}VR{\.I}KAYA {\c S}ER{\.I}FO{\u G}LU, FUNDA and Erol, Ismail and Nurtani{\c s} Velio{\u g}lu, Meltem}
}
@article {1461,
	title = {Life behavior of shock models for uniformly distributed interarrival times},
	journal = {Statistical Papers},
	volume = {55},
	year = {2014},
	month = {Aug},
	pages = {841{\textendash}852},
	issn = {0932-5026},
	author = {ERYILMAZ, SERKAN and K{\"o}n{\"u}l Bayramo{\u g}lu Kavlak}
}
@article {bacsdere2013leader,
	title = {A leader-follower game for the point coverage problem in wireless sensor networks},
	journal = {European Journal of Industrial Engineering},
	volume = {7},
	number = {5},
	year = {2013},
	pages = {635{\textendash}656},
	publisher = {Inderscience Publishers},
	author = {Ba{\c s}dere, Mehmet and Necati Aras and I. Kuban Altinel and Af{\c s}ar, Sezin}
}
@article {kuccukaydin2012leader,
	title = {A leader{\textendash}follower game in competitive facility location},
	journal = {Computers \& Operations Research},
	volume = {39},
	number = {2},
	year = {2012},
	pages = {437{\textendash}448},
	publisher = {Elsevier},
	author = {K{\"u}{\c c}{\"u}kayd{\i}n, Hande and Necati Aras and I. Kuban Altinel}
}
@article {keskin2011lifetime,
	title = {Lifetime maximization in wireless sensor networks using a mobile sink with nonzero traveling time},
	journal = {The Computer Journal},
	year = {2011},
	pages = {bxr048},
	publisher = {Oxford University Press},
	author = {Keskin, M Emre and I. Kuban Altinel and Necati Aras and Ersoy, Cem}
}
@conference {aras2010location,
	title = {Location and selective routing problem with pricing for the collection of used products},
	booktitle = {Computers and Industrial Engineering (CIE), 2010 40th International Conference on},
	year = {2010},
	pages = {1{\textendash}6},
	publisher = {IEEE},
	organization = {IEEE},
	author = {Necati Aras and Aksen, Deniz and Tekin, Tugrul}
}
@article {4778684,
	title = {{A location-allocation heuristic for the capacitated multi-facility Weber problem with probabilistic customer locations}},
	journal = {European Journal of Operational Research},
	volume = {198},
	year = {2009},
	pages = {790{\textendash}799},
	doi = {10.1016/j.ejor.2008.10.014},
	author = {I. Kuban Altinel and Engin Durmaz and Necati Aras and Kerem Can {\"O}zkisacik}
}
@article {Aras2008a,
	title = {Locating collection centers for distance-and incentive-dependent returns},
	journal = {International Journal of Production Economics},
	volume = {111},
	number = {2},
	year = {2008},
	pages = {316{\textendash}333},
	publisher = {Elsevier},
	author = {Necati Aras and Aksen, Deniz}
}
@article {Aras2008,
	title = {Locating collection centers for incentive-dependent returns under a pick-up policy with capacitated vehicles},
	journal = {European Journal of Operational Research},
	volume = {191},
	number = {3},
	year = {2008},
	pages = {1223{\textendash}1240},
	publisher = {Elsevier},
	author = {Necati Aras and Aksen, Deniz and G{\"o}n{\"u}l Tanu{\u g}ur, Ay{\c s}e}
}
@article {1491,
	title = {A location problem on unicyclic networks: Balanced case},
	journal = {European Journal of Operational Research},
	volume = {62},
	year = {1992},
	pages = {194-202},
	abstract = {<p>The problem of locating n stations on a unicyclic unidirectional network is considered. We formulated the problem as an integer program for the case of a balanced flow matrix, i.e., the total inflow to a station equals the total outflow from that station. The integer programming formulation reduces the problem to a station sequencing problem regardless of the actual station locations on the network. Furthermore, the empirical evidence suggests that the LP solutions to the relaxed IP formulations are optimal.</p>},
	issn = {0377-2217},
	doi = {https://doi.org/10.1016/0377-2217(92)90247-7},
	url = {https://www.sciencedirect.com/science/article/pii/0377221792902477},
	author = {Ali S. Kiran and Ali Tamer {\"U}nal and Selcuk Karabati}
}
