Understanding the resilience of strategic networks (SN): The case of an Italian 40-year-old SN

Nowadays, the design of a strategic supply chain network under the incidence of disruption is regarded as one of the important priorities of governments. Supplying sustainable petrochemical products is considered as a strategic goal by managers who require reliable infrastructure design. Crisis conditions such as natural disasters and sanctions have a destructive effect on the raw materials and product flows. On the other hand, the uncertainty of input parameters affects the business environment and intensifies the condition of disruption. In the present research, a new model of resilient supply chain network is introduced in a critical condition, which consists in a combination of reactive and preventive resilient strategies. In order to deal with the parametric uncertainties caused by changes in the business environment and inadequate knowledge, an effective hybrid possibilistic-flexible robust programming method was presented. The proposed model was capable of controlling the adverse effects of uncertainties and risk-aversion level of output decisions. The extended model was analyzed in the national project of polyethylene strategic supply chain network using real data, which included the flexibility of demand, capacity, and lead time components. The results indicated that optimality and feasibility robustness were guaranteed by presenting efficiency solutions.

Building back better: Modeling decentralized recovery in sociotechnical systems using strategic network dynamics

Nowadays, the management of soil resources for global food security is one of the strategic purposes of the countries. In this regard, creating soil nutrition’s supply chain network for the fertility of agricultural fields is one of the most critical priorities of the government. In the above strategic network, we are faced with uncertain parameters that show a complex behavior under time, geography, and market changes. This parametric uncertainty is aggravated by the occurrence of disruptions such as sanctions and natural disasters, with devastating effects on strategic, tactical, and operational decisions. In this paper, by adopting a set of reactive and preventive strategies, the resilient supply chain network of dependent petrochemical industries is presented, consistent with the structure of its production cycle in Iran. To cope with the uncertainty, a robust programming approach was extended into flexible-possibilistic programming. The final model controls the uncertainty and risk-aversion of output decisions and effectively confronts the adverse effects of disruptions. Finally, using a real industrial study, the effectiveness and applicability of the final model are explained. Furthermore, by providing efficient solutions, mean cost and minimum standard deviations were achieved.

Reliability analysis of the global graphite trade industry chain risk assessment based on percolation theory

The bidirectionality of networks makes them resilient, but also vulnerable to propagating failures from cyberattacks. Unidirectional systems are mostly immune to cyberattack. The radio navigation component of the Global Positioning System (GPS) is unidirectional. However, it may be assessed as a bidirectional network when it is used to provide equivalent information in place of terrestrial networks that have failed. GPS thus serves as a case study for a novel mathematical formulation of the contribution of space-based unidirectional systems to the resilience of strategic cyber networks. The technical basis for this formulation is a parametric model of the exceedance probability for N GPS satellites in view of a receiver. The exceedance probabilities form an N+1 node network whose spectral radius can be computed. Three resiliency attributes for space-based unidirectional networks that use the resulting spectral radii are examined: connectedness as a function of failure, unidirectionality, and directness.

Current flood risk assessment and decision support tools, the UK Planning Policy Statement 25 and the UK Environment Agency (EA) flood maps, focus on the areas directly affected by flooding; however they do not address the indirect consequences of flooding on the existing street network. Research has been done in transport network reliability and resilience to disasters but little application exists to the floods scenario. In this paper we introduce a methodology developed at Space Syntax Limited to analyse and visualise the wider impact of flooding on the urban street network, measuring its performance in order to respond to the situation more effectively. Starting from a hypothetical scenario of floods in London affecting the areas within the highest risk flood Zone 3 as defined by the EA, we use a spatial model of London up to the M25 circular motorway and run network analysis algorithms before and after the flooding. Using a GIS we quantify the extent to which flooding affects the global structure of the city and the spatial accessibility of town centres. The analysis also provides indicators of traffic level distributions to evaluate the performance of the strategic transport network revealing a dependency on the M25 in the flooded scenario for longer trips across London, suggesting congestion levels beyond its capacity. With this work we demonstrate that space syntax network analysis provides objective indicators to demonstrate the indirect impacts of flooding on urban street networks which can be used by relevant authorities to support a future vision and their investment decisions concerning preventative strategies, disaster management and repair.

How habitat loss and fragmentation are reducing conservation opportunities for vertebrates in the most threatened savanna of the World

Reinforcement Learning and Adaptive Optimal Control of Congestion Pricing

Operating roads are critical during emergency operations at a disaster area. Prolonged inundation of pavements accelerates rapid deterioration of pavements and increases maintenance cost. The upgrade of vulnerable pavements with a raised subgrade and gabion walls is proposed as the means to increase the resiliency of strategic roads vital during the emergency attention in the aftermath of a cyclone. Hence, optimal pavement management can be used to allocate upgrade and maintenance and rehabilitation (M&R) operations to reduce the damage and mitigate the geo-physical risk and community vulnerability before the disaster even occurs. A case study is presented for regional highways, arterial and collector roads of Barguna district in Bangladesh that is frequently affected by cyclones and storm surges. The geo-physical risk and vulnerability (GEOPHRIV) index of each road segments is estimated by integrating the geo-physical risk; community, structure and infrastructure vulnerabilities; and damage indices. Dynamic linear programming is applied to optimise M&R strategies and the conversion of strategic roads into resilient perpetual pavements. The same budget required to optimise roads condition is also used to guide the conversion of roads into perpetual pavements, therefore increasing the overall network resiliency. As expected, the results show that most of the annual budget is equally expended into the conversion or the resurfacing of pavements. The decision-making approach herein proposed is very useful to roads agencies around the world, because it provides them with the ability to increase the resiliency of their strategic network ex-ante any flooding disaster.

This paper introduces a framework for studying resilience of networked systems in the presence of strong network externalities. The framework used in this paper explicitly incorporates costs of connection and the benefits that are received by direct and indirect access to resources. We show that this simple framework is capable of capturing the three key parameters of resilience: Magnitude of Performance drop, transient to recovery and post recovery performance. We also show that the model can capture certain phase transitions as a result of single-node disruption. While we focus on homogeneous structures, assume efficiency, and consider only node failure, the framework can easily be used in modeling more general performance schemes and be extended to link failure or hybrid scenarios where both links and nodes are disrupted.

Campus handling of networks has become critical in the continuously changing world of higher education. This paper offers a thorough method for managing and safeguarding networks in a campus setting with multiple departments. Our approach focuses on four departments: the administrative, civil, computer science and engineering (CSE), and electrical and electronics engineering (EEE) departments. It combines multiple networking technologies to improve security and maximize speed. Network division using virtual LANs (VLANs), efficient IP address allocation using Variable Length Subnet Masks (VLSM), simplified network configuration using Dynamic Host Configuration Protocol (DHCP), dynamic routing using Routing Information Protocol version 2 (RIPv2), granular access control using Access Control Lists (ACLs), enhanced security using Network Address Translation (NAT), secure remote access using Secure Shell version 2 (SSHv2), and improved network resilience through Link Aggregation are the main components of our system.