Based on the emergence of the Internet of Things, smart logistic units (container, pallet, cardboard) offers a new opportunity to improve the responsiveness to disturbances of the supply chain and to develop robust scheduling approach based on the knowledge extracted from the historical data of traceability on the smart logistic units. The limitations of the current traceability solutions are related in particular to the insufficient level of detail, the late availability of data and the scattering of data in databases of different actors in the supply chain who are reluctant to exchange them. Then, the unitary traceability based on the Internet of Things with a real-time tracking of multiple parameters of each object (position, temperature, vibration, humidity, etc.) is a solution which makes it possible to improve reactivity in real time when facing disturbances and to extract knowledge from historical data. Therefore, this paper proposes a conceptual framework based on seven activities that exploit smart container traceability data for real-time analysis and decision to monitor risks of disruptions and to mitigate the impact of disruptions.

Emergency logistics is one of the most important parts of disaster relief operations. Quick and adequate decision making in this sector is vital but sometimes hard to achieve. This issue is currently faced by several humanitarian organizations, where the high turnover of staff and the lack of adequate tools make it hard to learn from past experiences. Choosing the most appropriate supplier, the adapted warehouse and transportation means is a complicated task. Indeed, on the one hand there are many criteria to take into account in the decision-making process, and on the other hand the relative importance of those criteria is changing over time. Existing academic works on this issue are very difficult to implement on real case scenarios as they do not propose practical solutions. In this paper, a decision model which evolves over time, depending on operations progresses is proposed. Selection of supplier, warehouse and vehicle are taken into consideration thanks to the Multi-Criteria Decision Making (MCDM) approach. In order to achieve a proper decision, Analytic Hierarchy Process (AHP) is used first to analyze the structure of alternatives selection problem and to determine weights of criteria. Then Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method is used to obtain final ranking in a four-phases of humanitarian operation life cycle. A numerical example based on preliminary data from the French Red Cross including the sensitivity analysis is presented to clarify and validate the methodology.

No abstract

No abstract

No abstract