A smart and agile dry port-seaport logistic network considering industry 5.0: A multi-stage data-driven approach

Abstract

The advent of Industry 5.0 (I5.0) has precipitated a demand for sophisticated technological solutions across diverse sectors, with a particular emphasis on logistics. Dry Port-Seaports (DPSs), playing a pivotal role in facilitating international trade, are poised to derive substantial advantages from this revolution, while limited attention has been dedicated to this subject matter. This work is among the first studies that present a multi-stage, multi-objective scenario-based programming model to design a logistics network of DPSs, considering a combination of an Internet of Things (IoT) based infrastructure and I5.0 principles. Several real-world characteristics, including tardiness, staff fatigue, Multi-Modal Transportation (MMT), interrupted capacity, and export/import forecasting, are integrated into the proposed model, as well. For this purpose, the potential locations of Dry Ports (DPs) are evaluated based on I5.0 dimensions by applying the Stochastic Best Worst Method (SBWM). Subsequently, the selected DPs are assessed regarding the deployment of Internet of Things (IoT) infrastructure. Eventually, a mathematical model is developed to design the DPS Logistic Network (LN) optimally. To tackle the developed mathematical model, an effective solving approach, called the Stochastic Fuzzy Meta Goal Programming (SFMGP) procedure, is introduced. Among the various time-series prediction models examined, the Seasonal Autoregressive Integrated Moving Average (SARIMA) model, characterized by a lower Akaike Information Criterion (AIC), is chosen to forecast demand, as well. In order to ascertain the efficacy of the proposed framework, a real case study from commercial ports of southern Iran has been undertaken. The obtained results illustrate that the deployment IoT-based systems has significant impacts on the prevention and management of disruptions; however it may necessitate a high initial investment outlay. Moreover, the integration of IoT technology within logistics networks offers avenues for optimizing efficiency, transparency, and decision-making procedures. To illustrate, the tardiness rate is reduced by 68 % and transparency is heightened by 71 % based on the results.