@article {1436,
	title = {Minimizing the misinformation spread in social networks},
	journal = {IISE Transactions},
	volume = {52},
	year = {2020},
	pages = {850-863},
	abstract = {<p>AbstractThe Influence Maximization Problem has been widely studied in recent years, due to rich application areas including marketing. It involves finding k nodes to trigger a spread such that the expected number of influenced nodes is maximized. The problem we address in this study is an extension of the reverse influence maximization problem, i.e., misinformation minimization problem where two players make decisions sequentially in the form of a Stackelberg game. The first player aims to minimize the spread of misinformation whereas the second player aims its maximization. Two algorithms, one greedy heuristic and one matheuristic, are proposed for the first player{\textquoteright}s problem. In both of them, the second player{\textquoteright}s problem is approximated by Sample Average Approximation, a well-known method for solving two-stage stochastic programming problems, that is augmented with a state-of-the-art algorithm developed for the influence maximization problem.</p>},
	doi = {10.1080/24725854.2019.1680909},
	url = {https://doi.org/10.1080/24725854.2019.1680909},
	author = {K{\"u}bra Tan{\i}nm{\i}{\c s} and Necati Aras and I. Kuban Altinel and Evren G{\"u}ney}
}
@article {1434,
	title = {Minimum cost noncrossing flow problem on layered networks},
	journal = {Discrete Applied Mathematics},
	volume = {261},
	year = {2019},
	pages = {2-21},
	abstract = {<p>In this work we focus on an extension of the minimum cost flow problem in layered networks. Feasible arc flows must satisfy a specific compatibility restriction in addition to flow balance and capacity restrictions. Namely, at most one of the crossing arcs is allowed to have positive flow on it. This variant of the minimum cost flow problem, which we call the minimum cost noncrossing flow problem, can frequently be encountered in real life. The determination of optimal temporal quay crane allocations to berthed vessels in container terminals, and optimal train schedules through the stations on the same railroad line are two examples. We first analyze the complexity of the problem and show that the noncrossing flow problem is in fact NP-complete in a layered network. Then, we introduce mixed-integer linear programming formulations and discuss a polynomially solvable special case. Next we show a sufficient condition for the existence of a crossing in an optimal solution, which can be used for preprocessing the arcs in order to reduce the problem size. Our computational experiments on a large test set show that our preprocessing algorithm can significantly reduce the number of arcs.</p>},
	keywords = {integer programming, Layered networks, Network flows, Noncrossing flow},
	issn = {0166-218X},
	doi = {https://doi.org/10.1016/j.dam.2018.09.016},
	url = {https://www.sciencedirect.com/science/article/pii/S0166218X18304815},
	author = {I. Kuban Altinel and Necati Aras and Zeynep {\c S}uvak and Z C Ta{\c s}k{\i}n}
}
@inbook {aksen2013matheuristic,
	title = {A Matheuristic for Leader-Follower Games Involving Facility Location-Protection-Interdiction Decisions},
	booktitle = {Metaheuristics for Bi-level Optimization},
	year = {2013},
	pages = {115{\textendash}151},
	publisher = {Springer Berlin Heidelberg},
	organization = {Springer Berlin Heidelberg},
	author = {Aksen, Deniz and Necati Aras}
}
