@ARTICLE{SK2017,
	author={Sifaleras, A., Konstantaras, I.},
	title={Variable neighborhood descent heuristic for solving reverse logistics multi-item dynamic lot-sizing problems},
	journal={Computers and Operations Research},
	year={2017},
	volume={78},
	pages={385--392},	
	url={http://dx.doi.org/10.1016/j.cor.2015.10.004},
	pdf = {./papers/Variable_neighborhood_descent_heuristic_for_solving_reverse_logistics_multi-item_dynamic_lot-sizing_problems.pdf},
	abstract = {The multi-product dynamic lot sizing problem with product returns and recovery is an important problem that appears in reverse logistics and is known to be NP-hard. In this paper we propose an efficient variable neighborhood descent heuristic algorithm for solving this problem. Furthermore, we present a new benchmark set with the largest instances in the literature. The computational results demonstrate that our approach outperforms the state-of-the-art Gurobi optimizer.}
}

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