Towards Modelling of Evacuation Behavior and Planning for Emergency Logistics Due to the Philippine Taal Volcanic Eruption in 2020

Emergency evacuation is the immediate escape of people away from a place of an imminent threat to a place of safety. The ability of the households to evacuate is a crucial component in reducing disaster risk. Logistical issues such as a lack of resources during and after the evacuation, as well as road congestion, might arise, especially in short and no-notice calamities such as a volcanic eruption. This study examines the relationship of variables of evacuation logistics of Barangay Banga, Talisay, Batangas in the context of the 2020 Taal Volcanic eruption. A survey was conducted based on the experience of the households during the volcanic eruption. A descriptive statistical analysis was performed for all the variables on household evacuation logistics to understand the behavior of households as they make decisions during emergencies. These variables include the type of evacuation, departure timing, evacuation mode choice, and destination choice. Additionally, a pairwise correlation was employed to identify the influential factors related to household evacuation logistics such as socio-demographic and household characteristics, hazard-related factors as well as their experience with Taal Volcano’s recurring activities. The results of this study aim to provide insights to a better understanding of the evacuation behavior of households in the context of a volcanic eruption and be useful in the evacuation logistics planning of the country.

Research on Emergency Logistics Model of Agricultural Products Based on Coupling of Petri Net and Blockchain

In this COVID-19 epidemic, due to insufficient awareness of the impact of sudden public health emergencies on agricultural logistics at this stage, agricultural products were left unsold, stocks were backlogged, and losses were severe. In the process of distribution, we should not only ensure a short time cycle and avoid the contamination of agricultural products by foreign bacteria, but also pay attention to the waste of human, material, and financial resources. Therefore, this study mainly adopts the combination of the petrochemical network and block chain to build an agricultural products emergency logistics model. This paper first shows the operation mechanism of the petri dish network and blockchain coupling in the form of a graph and then uses the culture network modelling and simulation tool PIPE to directly verify the construction model. It is proved that the structure and overall business process of the agricultural products logistics system constructed by combining the Petri net and block chain are reasonable, reliable, and feasible in practical application and development. It is hoped that this study can provide a reference direction for agricultural emergency logistics.

Multi-attribute decision making method based on probabilistic linguistic term sets and its application in the evaluation of emergency logistics capacity

The occurrence of public health emergency will cause huge economic losses and casualties, which posed a huge threat to the economic and social development. In response to the emergency, a large amount of emergency relief supplies will be transported to the affected areas. Faced with this public health emergency of international concern, the concept of emergency logistics capacity and the evaluation model based on probabilistic linguistic term sets are proposed. In this paper, the emergency logistics capability evaluation is transformed into user demand evaluation, and the importance of each index of emergency logistics capability is determined by using Quality Function Deployment (QFD) and prospect theory. Under the probabilistic language information environment, a multi-attribute decision making method is established by using TODIM method. Finally, an example is given to verify the feasibility of the proposed method.

Research on Decision Model of Emergency Material Distribution Based on Random Information

As an important link of emergency logistics, emergency material distribution has been widely concerned and applied in the development of today’s society. From the consideration of the fairness and efficiency of material distribution, there is a kind of negative and negative relationship between them. As a lever, information updating can be used to solve the problems of fairness and efficiency in the distribution of emergency supplies. Based on fuzzy objective programming, the classification decision model of emergency materials is discussed in this paper.

A Novel Hybrid Algorithm for Multiobjective Location-Allocation Problem in Emergency Logistics

Increased frequency of disasters keeps reminding us of the importance of effective resource distribution in postdisaster. To reduce the suffering of victims, this paper focuses on how to establish an effective emergency logistics system. We first propose a multiobjective optimization model in which the location and allocation decisions are made for a three-level logistics network. Three objectives, deprivation costs, unsatisfied demand costs, and logistics cost, are adopted in the proposed optimization model. Several cardinality and flow balance constraints are considered simultaneously. Then, we design a novel effective IFA-GA algorithm by combining the firefly algorithm and genetic algorithm to solve this complex model effectively. Furthermore, three schemes are proposed to improve the effectiveness of the IFA-GA algorithm. Finally, the numerical results provide several insights on the theory and practice of relief distribution, which also illustrate the validity of the proposed solution algorithm.

Distribution of the Emergency Supplies in the COVID-19 Pandemic: A Cloud Computing Based Approach

The containment of the COVID-19 pandemic was significantly affected by the unbalanced distribution of emergency supplies, low coordinated transport efficiency, high costs, and the inability of nonprofit organizations to handle the emergency supplies efficiently. Based on the COVID-19 experience, in this paper, we build a cloud platform for emergency supplies distribution to reduce the asymmetry of emergency logistics information, reduce the costs, and improve the efficiency of emergency supplies distribution. Our proposed method uses a genetic algorithm with the monarch scheme to optimize the urban emergency supplies distribution. The numerical results and sensitivity analysis for a sample network indicate that using the proposed platform the integrated cost in different cities are reduced by 29.01%, 28.67%, and 22.73%, the required time in different cities are reduced by 22.98%, 26.59%, and 36.65%. The results suggest that the proposed method reduces the integrated cost and transportation time and finds the optimal distribution path.