Facility planning and schedule design in the pandemic: Eliminating contacts at construction workplace.

The construction industry has been severely affected by the COVID-19 pandemic and the associated restrictions on person-to-person contacts issued by the government. A construction site usually has a high number of workers working at the same time; therefore, the question of how to ensure their safety during the pandemic-that is, how to protect them from getting infected-has become an urgent problem. In this study, we propose a bi-objective integer programming model to establish the optimal schedule plan under COVID-19 regulations. We develop a solution method and conduct numerical experiments to solve and validate our model. The optimal schedule plan can avoid contacts between workers of different groups while minimizing the total costs of complying with government policy. Our proposed model can be applied in practice to help project managers establish a reasonable and cost-effective schedule plan. This study contributes to reducing the operating costs of contractors and protecting the health of construction workers.

Is port state control influenced by the COVID-19? Evidence from inspection data.

Maritime transport plays a key role in global trade. The safeguard of maritime transport is the Port State Control (PSC) inspection implemented all over the world. The outbreak of the Coronavirus disease (COVID-19) in 2020 presents new and unprecedented impacts on global supply chains and the ports as well as the entire shipping industry. Various measures were adopted by the countries and regions to halt the spread of the pandemic, mainly by reducing face-to-face interactions. As PSC inspections involve getting onboard vessels and in-person communications between the inspectors and the crew, its procedure and results are highly likely to be influenced by the COVID-19. This study aims to explore whether, how, and why the global and regional PSC inspection statuses are influenced by the pandemic through analyzing real inspection data. Specifically, three general indicators, namely inspection number, average deficiency number per inspection, and detention rate, are considered. Moreover, a detailed and comprehensive analysis of the inspection data at the Hong Kong port is conducted, including the number of inspections conducted, the average deficiency number and detention rate, the types of inspections conducted and ships inspected, the detailed deficiency and detention conditions, the relationship between the local pandemic situation and the PSC inspection status, and regression analysis on the influencing factors on inspection outcome. It is found that the COVID-19 pandemic indeed has an impact on PSC. Meanwhile, pragmatic and flexible measures are adopted by the port states, and the PSC has always been acting as a 'safety net' to guarantee maritime safety, promote the marine environment, and protect the seafarers' rights even under the difficult times during the COVID-19 pandemic.

A systematic review of prediction methods for emergency management

With the trend of global warming and destructive human activities, the frequent occurrences of catastrophes have posed devastating threats to human life and social stability worldwide. The emergency management (EM) system plays a significant role in saving people's lives and reducing property damage. The prediction system for the occurrence of emergency events and resulting impacts is widely recognized as the first stage of the EM system, the accuracy of which has a significant impact on the efficiency of resource allocation, dispatching, and evacuation. In fact, the number and variety of contributions to prediction techniques, such as statistic analysis, artificial intelligence, and simulation method, are exploded in recent years, motivating the need for a systematic analysis of the current works on disaster prediction. To this end, this paper presents a systematic review of contributions on prediction methods for emergency occurrence and resource demand of both natural and man-made disasters. Through a detailed discussion on the features of each type of emergency event, this paper presents a comprehensive survey of state-of-the-art prediction technologies which have been widely applied in EM. After that, we summarize the challenges of current efforts and point out future directions.