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Cortinhal, M. J., Lopes, M. J. & Melo, M. T. (2015). Dynamic design and re-design of multi-echelon, multi-product logistics networks with outsourcing opportunities: a computational study. Computers and Industrial Engineering. 90, 118-131

M. J. Cortinhal et al.,  "Dynamic design and re-design of multi-echelon, multi-product logistics networks with outsourcing opportunities: a computational study", in Computers and Industrial Engineering, vol. 90, pp. 118-131, 2015

@article{cortinhal2015_1734885120642,
	author = "Cortinhal, M. J. and Lopes, M. J. and Melo, M. T.",
	title = "Dynamic design and re-design of multi-echelon, multi-product logistics networks with outsourcing opportunities: a computational study",
	journal = "Computers and Industrial Engineering",
	year = "2015",
	volume = "90",
	number = "",
	doi = "10.1016/j.cie.2015.08.019",
	pages = "118-131",
	url = "http://www.sciencedirect.com/science/article/pii/S0360835215003551"
}

TY  - JOUR
TI  - Dynamic design and re-design of multi-echelon, multi-product logistics networks with outsourcing opportunities: a computational study
T2  - Computers and Industrial Engineering
VL  - 90
AU  - Cortinhal, M. J.
AU  - Lopes, M. J.
AU  - Melo, M. T.
PY  - 2015
SP  - 118-131
SN  - 0360-8352
DO  - 10.1016/j.cie.2015.08.019
UR  - http://www.sciencedirect.com/science/article/pii/S0360835215003551
AB  - We address the problem of designing/redesigning a multi-echelon logistics network over multiple periods. Strategic decisions comprise opening new facilities and selecting their capacities from a set of available discrete sizes. Capacity expansion may occur more than once over the time horizon both at new locations and at existing facilities. In addition, logistics decisions involving supplier selection, procurement, production, and distribution of multiple products are to be made. The latter also involve the choice of transportation modes with limited capacities. Finally, a strategic choice between in-house manufacturing and a mixed approach with product outsourcing is to be taken. We propose a mixed-integer linear programming model and develop additional inequalities to enhance the original formulation. To gain insight into the complexity of the problem at hand, an extensive computational study is performed with randomly generated instances that are solved with standard mathematical optimization software. Useful managerial insights are derived from varying several parameters and analyzing the impact of different business strategies on various segments of the logistics network.
ER  -