ABSTRACT
Wireless body area networks (WBANs) are helpful for remote health monitoring, especially during the COVID-19 pandemic. Due to the limited batteries of bio-sensors, energy-efficient routing is vital to achieve load-balancing and prolong the network's lifetime. Although many routing techniques have been presented for WBANs, they were designed for an application, and their performance may be degraded in other applications. In this paper, an ensemble Metaheuristic-Driven Machine Learning Routing Protocol (MDML-RP) is introduced as an adaptive real-time remote health monitoring in WBANs. The motivation behind this technique is to utilize the superior route optimization solutions offered by metaheuristics and to integrate them with the real-time routing capability of machine learning. The proposed method involves two phases: offline model tuning and online routing. During the offline pre-processing step, a metaheuristic algorithm based on the whale optimization algorithm (WOA) is used to optimize routes across various WBAN configurations. By applying WOA for multiple WBANs, a comprehensive dataset is generated. This dataset is then used to train and test a machine learning regressor that is based on support vector regression (SVR). Next, the optimized MDML-RP model is applied as an adaptive real-time protocol, which can efficiently respond to just-in-time requests in new, previously unseen WBANs. Simulation results in various WBANs demonstrate the superiority of the MDML-RP model in terms of application-specific performance measures when compared with the existing heuristic, metaheuristic, and machine learning protocols. The findings indicate that the proposed MDML-RP model achieves noteworthy improvement rates across various performance metrics when compared to the existing techniques, with an average improvement of 42.3% for the network lifetime, 15.4% for reliability, 31.3% for path loss, and 31.7% for hot-spot temperature.
ABSTRACT
Blood platelets are a typical instance of perishable age-differentiated products with a shelf life of five days (on average), which may lead to significant wastage of some collected samples. At the same time, a shortage of platelets may also be observed because of emergency demands and the limited number of donors, especially during disasters such as wars and the COVID-19 pandemic. Therefore, developing an efficient blood platelet supply chain management model is highly necessary to reduce shortage and wastage. In this research, an integrated resilient–sustainable supply chain network of perishable age-differentiated platelets considering vertical and horizontal transshipment is designed. In order to achieve sustainability, economic cost, social cost (shortage), and environmental cost (wastage) are taken into account. A reactive resilient strategy utilizing lateral transshipment between hospitals is adopted to make the blood platelet supply chain powerful against shortage and disruption risks. The presented model is solved using a metaheuristic based on a local search-empowered grey wolf optimizer. The obtained results demonstrate the efficiency of the proposed vertical–horizontal transshipment model in reducing total economic cost, shortage, and wastage by 3.61%, 30.1%, and 18.8%, respectively.
ABSTRACT
Blood platelets are a typical instance of perishable age-differentiated products with a shelf life of five days (on average), which may lead to significant wastage of some collected samples. At the same time, a shortage of platelets may also be observed because of emergency demands and the limited number of donors, especially during disasters such as wars and the COVID-19 pandemic. Therefore, developing an efficient blood platelet supply chain management model is highly necessary to reduce shortage and wastage. In this research, an integrated resilient-sustainable supply chain network of perishable age-differentiated platelets considering vertical and horizontal transshipment is designed. In order to achieve sustainability, economic cost, social cost (shortage), and environmental cost (wastage) are taken into account. A reactive resilient strategy utilizing lateral transshipment between hospitals is adopted to make the blood platelet supply chain powerful against shortage and disruption risks. The presented model is solved using a metaheuristic based on a local search-empowered grey wolf optimizer. The obtained results demonstrate the efficiency of the proposed vertical-horizontal transshipment model in reducing total economic cost, shortage, and wastage by 3.61%, 30.1%, and 18.8%, respectively.