A Robust Mixed-Integer Linear Programming Model for Sustainable Collaborative Distribution

In this paper, we propose robust optimisation models for the distribution network design problem (DNDP) to deal with uncertainty cases in a collaborative context. The studied network consists of collaborative suppliers who satisfy their customers’ needs by delivering their products through common pl...

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Vydáno v:	Mathematics (Basel) Ročník 9; číslo 18; s. 2318
Hlavní autoři:	Snoussi, Islem, Hamani, Nadia, Mrabti, Nassim, Kermad, Lyes
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Basel MDPI AG 01.09.2021 MDPI
Témata:	Algorithms Carbon dioxide Collaboration Costs COVID-19 Decomposition distribution network design problem (DNDP) Emissions Engineering Sciences Heuristic horizontal collaboration Integer programming Linear programming Literature reviews Logistics Mathematical programming Mathematics Mixed integer mixed-integer linear programming Network design Operating costs Optimization Random variables robust optimisation Robustness Sustainability Uncertainty uncertainty budget horizontal collaboration robust optimisation distribution network design problem (DNDP) uncertainty budget sustainability mixed-integer linear programming
ISSN:	2227-7390, 2227-7390
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Abstract	In this paper, we propose robust optimisation models for the distribution network design problem (DNDP) to deal with uncertainty cases in a collaborative context. The studied network consists of collaborative suppliers who satisfy their customers’ needs by delivering their products through common platforms. Several parameters—namely, demands, unit transportation costs, the maximum number of vehicles in use, etc.—are subject to interval uncertainty. Mixed-integer linear programming formulations are presented for each of these cases, in which the economic and environmental dimensions of the sustainability are studied and applied to minimise the logistical costs and the CO2 emissions, respectively. These formulations are solved using CPLEX. In this study, we propose a case study of a distribution network in France to validate our models. The obtained results show the impacts of considering uncertainty by comparing the robust model to the deterministic one. We also address the impacts of the uncertainty level and uncertainty budget on logistical costs and CO2 emissions.
AbstractList	In this paper, we propose robust optimisation models for the distribution network design problem (DNDP) to deal with uncertainty cases in a collaborative context. The studied network consists of collaborative suppliers who satisfy their customers' needs by delivering their products through common platforms. Several parameters-namely, demands, unit transportation costs, the maximum number of vehicles in use, etc.-are subject to interval uncertainty. Mixed-integer linear programming formulations are presented for each of these cases, in which the economic and environmental dimensions of the sustainability are studied and applied to minimise the logistical costs and the CO2 emissions, respectively. These formulations are solved using CPLEX. In this study, we propose a case study of a distribution network in France to validate our models. The obtained results show the impacts of considering uncertainty by comparing the robust model to the deterministic one. We also address the impacts of the uncertainty level and uncertainty budget on logistical costs and CO2 emissions.
Author	Mrabti, Nassim Hamani, Nadia Kermad, Lyes Snoussi, Islem
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Cites_doi	10.1080/00207543.2019.1574040 10.1007/s40092-019-00329-9 10.1109/ACCESS.2020.2985377 10.1515/9781400831050 10.1016/j.tre.2018.09.002 10.1016/j.ejor.2011.02.018 10.1007/s10107-003-0396-4 10.1007/978-3-030-85969-5_4 10.1016/j.trb.2016.01.010 10.1504/IJSCIM.2017.086371 10.1016/j.cie.2017.06.017 10.5267/j.uscm.2019.12.001 10.1016/j.trb.2011.11.006 10.1016/j.cie.2018.07.028 10.1016/j.trb.2016.01.011 10.1007/s40314-014-0179-y 10.1016/j.ejor.2019.06.047 10.1016/j.omega.2017.01.011 10.1007/978-3-642-05465-5_3 10.3390/su13073891 10.1016/j.cor.2017.08.001 10.1016/j.cor.2018.04.021 10.1007/b137941 10.1016/j.trb.2017.06.008 10.1287/trsc.2018.0871 10.1016/j.jairtraman.2015.06.001 10.1007/s40314-020-01405-2
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SubjectTerms	Algorithms Carbon dioxide Collaboration Costs COVID-19 Decomposition distribution network design problem (DNDP) Emissions Engineering Sciences Heuristic horizontal collaboration Integer programming Linear programming Literature reviews Logistics Mathematical programming Mathematics Mixed integer mixed-integer linear programming Network design Operating costs Optimization Random variables robust optimisation Robustness Sustainability Uncertainty uncertainty budget
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Title	A Robust Mixed-Integer Linear Programming Model for Sustainable Collaborative Distribution
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