@article {1587,
	title = {A reference set based many-objective co-evolutionary algorithm with an application to the knapsack problem},
	journal = {European Journal of Operational Research},
	volume = {300},
	year = {2022},
	pages = {405{\textendash}417},
	doi = {10.1016/j.ejor.2021.10.033},
	url = {https://doi.org/10.1016/j.ejor.2021.10.033}
}
@article {1586,
	title = {A robust disaster preparedness model for effective and fair disaster response},
	journal = {European Journal of Operational Research},
	volume = {280},
	year = {2020},
	pages = {479{\textendash}494},
	doi = {10.1016/j.ejor.2019.07.029},
	url = {https://doi.org/10.1016/j.ejor.2019.07.029}
}
@article {1442,
	title = {Robust supply chain network design with multi-products for a company in the food sector},
	journal = {Applied Mathematical Modelling},
	volume = {60},
	year = {2018},
	pages = {526-539},
	abstract = {<p>The paper aims to solve a problem faced by a company competing in the snacks market in Turkey. In line with the growth in this market, the company needs to make important decisions over the next few years about the timing and location of a new plant, its initial capacity, the timing and amount of additional capacity to be installed at the new and existing plants, the assignment of demand points to plants and the amount of raw materials to be shipped from suppliers to the plants in each period. The objective is to minimize the total cost of various components. The problem is formulated as a multi-period supply chain network design model with multi products. The resulting mixed-integer linear programming model is solved by the commercial solver CPLEX. This model enables us to carry out all analyses requested by the company in an efficient way. After this deterministic model is solved on the basis of a 9\% annual increase in demand, it is extended to a minimax regret model to deal with uncertainty in demand quantities. The results suggest that opening the new plant in the city of {\.I}zmir is indeed a robust solution that is unaffected in different scenarios that are based on three distinct demand increase rates. Even though the location of the new plant remains unchanged with respect to scenarios, the optimal robust solution differs from the optimal solution of each scenario in terms of the capacity expansion decisions. After all obtained results had been communicated to the company managers and executives, the new plant construction was started in 2016 very close to the city that the mathematical model had determined. The new plant is expected to start operating in 2018.</p>},
	keywords = {Demand uncertainty, Facility location-allocation, Mixed-integer linear programming, Robust optimization, Supply chain network design},
	issn = {0307-904X},
	doi = {https://doi.org/10.1016/j.apm.2018.03.034},
	url = {https://www.sciencedirect.com/science/article/pii/S0307904X18301586},
	author = {Necati Aras and {\"U}mit Bilge}
}
@article {becsikci2013resource,
	title = {Resource dedication problem in a multi-project environment},
	journal = {Flexible Services and Manufacturing Journal},
	volume = {25},
	number = {1-2},
	year = {2013},
	pages = {206{\textendash}229},
	publisher = {Springer},
	author = {Be{\c s}ikci, Umut and {\"U}mit Bilge and Ulusoy, G{\"u}nd{\"u}z}
}
