Title of article :
Multi-echelon green open-location-routing problem: A robust-based stochastic optimization approach
Author/Authors :
Vakili, R Department of Economic - Kharazmi University - Tehran, Iran , Akbarpour Shirazi, M Department of Industrial Engineering and Management Systems - Amirkabir University of Technolog - Tehran, Iran , Gitinavard, H Department of Industrial Engineering and Management Systems - Amirkabir University of Technolog - Tehran, Iran
Abstract :
In recent years, it has been proven that promoting and observing environmental
competence could play an instrumental role in enhancing companies/countries'
industries in terms of sustainable development. In this study, a Green Open Location-
Routing Problem with Simultaneous Pickup and Delivery (GOLRPSPD) is considered
to minimize general costs. In addition to the signicance of cost minimization, the
objective function aims at promoting environmental competency in terms of the costs of
CO2 emissions and fuel consumptions. Meanwhile, in a complex situation, using precise
information could yield unreliable results in which considering uncertainty theories could
prevent data loss. In this respect, this study assumed the pickup and delivery demand
and travel time as probabilistic parameters. To address the issue, a robust stochastic
programming approach was developed to reduce the deviations of imprecise information.
Moreover, the proposed approach was applied based on ve scenarios to decide the best
decision in dierent situations. In addition, a practical example of the multi-echelon openlocation-
routing model was provided to represent the feasibility and applicability of the
presented robust stochastic programming approach. Finally, comparative and sensitivity
analyses were carried out to demonstrate the validity of the proposed approach and, also, to
point out the robustness and sensitiveness of the obtained results regarding some signicant
parameters.
Keywords :
Uncertainty , Open-location-routing problem , Green logistic , Stochastic programming , Robust optimization
Journal title :
Scientia Iranica(Transactions E: Industrial Engineering)