Waste management in health institutions has become important in recent years because of the increase in population and industrialisation. Waste generated from health institutions has risks for human health and the environment. Therefore, this paper presents a reverse logistics optimisation for waste collection and disposal in Turkish health institutions. A multiperiod, multitype product waste reverse logistics network was designed to build an effective collection and disposal system for waste generated from health institutions in Turkey. A mixed integer linear programming model was developed to determine the optimal number and locations of the facilities for efficient waste management in health care by minimising the total cost. In this context, a sensitivity analysis was conducted to examine the impact of the incremental changes of waste amounts on the optimal reverse logistics network. According to increasing waste amounts, the numbers of changes in facilities are analysed and strategies are specified.

Radio frequency identification (RFID) is a promising technology for optimising supply chain processes, as it improves manufacturing and retail operations from forecasting demand to planning, managing inventory, and distribution. In this study, a simulation model is used to calculate the net present value (NPV) of an RFID investment on a three-echelon supply chain and to examine the effects of sharing the tagging cost between supply chain members on the NPV at the echelon level. In the proposed model, NPVs for the retailer, distributor, and manufacturer are calculated for two cases. In the first case, the tagging cost is shared according to the expected benefit of each supply chain member using the tagging cost sharing factor. In the second case, the tagging cost is shared equally between supply chain members. Furthermore, we investigate the difference in the NPVs for a supply chain member change as the end-customer demand value increases.

Planning emergency evacuation operations in a proactive manner in public marine transportation systems is a critical success factor for passenger and crew safety. Despite the fact that there is a growing attention on safety issues for marine transportation systems, providing a real-time decision support for evacuation planning under different emergency conditions has not yet been addressed. In this context, this paper contributes to the related literature by providing a comprehensive methodology including simulation and statistical analysis along with a three-module decision support system (DSS) for ferryboat emergency evacuation. Emergency evacuation and fire environment are simulated via Maritime EXODUS V5.1 and SMARTFIRE V4.3, respectively. The methodology is applied to a real-life Ro-Ro ferry, and the results not only revealed significant factors on emergency evacuation performance, but also demonstrated the validity of the developed decision support system.

Marine transportation is a vital component of the world’s economy and transportation network. The number of people using passenger ships around the globe is increasing worldwide. Similar to other transportation systems, passenger safety is critical in maritime shipment. As emergency evacuation processes for ships are highly different from and more complicated than those for buildings and other vehicles, many researchers have published a vast range of documents related to this peculiar research area. However, there is a tangible lack of sufficient literature review studies that investigate marine emergency evacuation (MEE). That being the case, the potential of marine transportation and the effect of emergency evacuation operation on life safety have inspired the proposal of this study. This paper offers a review of the available literature on MEE modelling, analysis and planning during the period from 1973 to 2017 using a systematic approach. After reviewing relevant academic journals, peer-reviewed conference papers, and technical reports of agencies, relevant literature is analysed. In addition, the literature review is extended by means of proposing a framework methodology which considers different possible conditions and situations during MEE. Finally, insights for ship managers and policymakers are discussed and potential future research directions are identified.