@article {1446,
	title = {Gradual covering location problem with multi-type facilities considering customer preferences},
	journal = {Computers \& Industrial Engineering},
	volume = {147},
	year = {2020},
	pages = {106577},
	abstract = {<p>In this paper, we address a discrete facility location problem where a retailer aims at locating new facilities with possibly different characteristics. Customers visit the facilities based on their preferences which are represented as probabilities. These probabilities are determined in a novel way by using a fuzzy clustering algorithm. It is assumed that the sum of the probabilities with which customers at a given demand zone patronize different types of facilities is equal to one. However, among the same type of facilities they choose the closest facility, and the strength at which this facility covers the customer is based on two distances referred to as full coverage distance and gradual (partial) coverage distance. If the distance between the customer location and the closest facility is smaller (larger) than the full (partial) coverage distance, this customer is fully (not) covered, whereas for all distance values between full and partial coverage, the customer is partially covered. Both distance values depend on both the customer attributes and the type of the facility. Furthermore, facilities can only be opened if their revenue exceeds a certain threshold value. A final restriction is incorporated into the model by defining a minimum separation distance between the same facility types. This restriction is also extended to the case where a minimum threshold distance exists among facilities of different types. The objective of the retailer is to find the optimal locations and types of the new facilities in order to maximize its profit. Two versions of the problem are formulated using integer linear programming, which differ according to whether the minimum separation distance applies to the same facility type or different facility types. The resulting integer linear programming models are solved by three approaches: commercial solver CPLEX, heuristics based on Lagrangean relaxation, and local search implemented with 1-Add and 1-Swap moves. Apart from experimentally assessing the accuracy and the efficiency of the solution methods on a set of randomly generated test instances, we also carry out sensitivity analysis using a real-world problem instance.</p>},
	keywords = {Customer preferences, Facility location, Fuzzy c-means clustering, Gradual coverage, Lagrangean relaxation},
	issn = {0360-8352},
	doi = {https://doi.org/10.1016/j.cie.2020.106577},
	url = {https://www.sciencedirect.com/science/article/pii/S0360835220303119},
	author = {Hande K{\"u}{\c c}{\"u}kaydin and Necati Aras}
}
@article {1504,
	title = {Graphs of Edge-Intersecting Non-Splitting Paths in a Tree: Representations of Holes-Part II},
	journal = {Discrete Mathematics and Theoretical Computer Science},
	volume = {20},
	year = {2018},
	pages = {1b{\textendash}1b},
	author = {Boyac{\i}, Arman and Ekim, Tinaz and Shalom, Mordechai and Zaks, Shmuel}
}
@article {1170,
	title = {Graphs of edge-intersecting non-splitting paths in a tree: Representations of holes{\textemdash}Part I},
	journal = {Discrete Applied Mathematics},
	volume = {215},
	year = {2016},
	pages = {47{\textendash}60},
	author = {Boyac{\i}, Arman and Ekim, Tinaz and Shalom, Mordechai and Zaks, Shmuel}
}
@article {hormann2013generating,
	title = {Generating generalized inverse Gaussian random variates},
	journal = {Statistics and Computing},
	year = {2013},
	pages = {1{\textendash}11},
	publisher = {Springer US},
	author = {Wolfgang H{\"o}rmann and Leydold, Josef}
}
@article {boyaci2013graphs,
	title = {Graphs of Edge-Intersecting Non-splitting Paths in a Tree: Towards Hole Representations},
	year = {2013},
	author = {Boyac{\i}, Arman and Ekim, Tinaz and Shalom, Mordechai and Zaks, Shmuel}
}
@article {dingecc2012general,
	title = {A general control variate method for option pricing under L{\'e}vy processes},
	journal = {European Journal of Operational Research},
	volume = {221},
	number = {2},
	year = {2012},
	pages = {368{\textendash}377},
	publisher = {North-Holland},
	author = {Dinge{\c c}, Kemal Din{\c c}er and Wolfgang H{\"o}rmann}
}
@article {leydold2011generating,
	title = {Generating generalized inverse Gaussian random variates by fast inversion},
	journal = {Computational Statistics \& Data Analysis},
	volume = {55},
	number = {1},
	year = {2011},
	pages = {213{\textendash}217},
	publisher = {North-Holland},
	author = {Leydold, Josef and Wolfgang H{\"o}rmann}
}
@article {barlas2006goal,
	title = {Goal setting, evaluation, learning and revision: A dynamic modeling approach},
	journal = {Evaluation and Program Planning},
	volume = {29},
	number = {1},
	year = {2006},
	pages = {79{\textendash}87},
	publisher = {Elsevier},
	author = {Barlas, Yaman and Yasarcan, Hakan}
}
@article {yasarcan2005generalized,
	title = {A generalized stock control formulation for stock management problems involving composite delays and secondary stocks},
	journal = {System dynamics review},
	volume = {21},
	number = {1},
	year = {2005},
	pages = {33{\textendash}68},
	publisher = {Wiley Online Library},
	author = {Yasarcan, Hakan and Barlas, Yaman}
}
@conference {yasarcan2003general,
	title = {A general stock control formulation for stock management problems involving delays and secondary stocks},
	booktitle = {The 21st International System Dynamics Conference, New York City, USA},
	year = {2003},
	publisher = {System Dynamics Society (http://www.systemdynamics.org/conferences/2003/index.htm)},
	organization = {System Dynamics Society (http://www.systemdynamics.org/conferences/2003/index.htm)},
	author = {Yasarcan, Hakan and Barlas, Yaman}
}
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	volume = {25},
	year = {2001},
	pages = {371{\textendash}389},
	doi = {10.1016/S0098-1354(00)00663-3},
	author = {Seza Or{\c c}un and I. Kuban Altinel and {\"O}ner Horta{\c c}su}
}
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	year = {2001},
	pages = {519{\textendash}533},
	author = {S{\"u}leyman {\"O}zekici and I. Kuban Altinel and M. E. Angun}
}
@article {ulusoy1997genetic,
	title = {A genetic algorithm approach to the simultaneous scheduling of machines and automated guided vehicles},
	journal = {Computers \& Operations Research},
	volume = {24},
	number = {4},
	year = {1997},
	pages = {335{\textendash}351},
	publisher = {Elsevier},
	author = {Ulusoy, G{\"u}nd{\"u}z and Sivrikaya-{\c S}erifoǧlu, Funda and {\"U}mit Bilge}
}
@article {Hoermann:1993a,
	title = {The generation of binomial random variates},
	journal = {J. Stat. Comput. Simulation},
	volume = {46},
	number = {1{\textendash}2},
	year = {1993},
	pages = {101{\textendash}110},
	keywords = {binomial distribution, binomial random variates, fast rejection algorithm, random numbers, transformed rejection method},
	author = {Wolfgang H{\"o}rmann}
}
