The State-of-the-Art Survey on Optimization Methods for Cyber-physical Networks

Cyber-Physical Systems (CPS) are increasingly complex and frequently integrated into modern societies via critical infrastructure systems, products, and services. Consequently, there is a need for reliable functionality of these complex systems under various scenarios, from physical failures due to aging, through to cyber attacks. Indeed, the development of effective strategies to restore disrupted infrastructure systems continues to be a major challenge. Hitherto, there have been an increasing number of papers evaluating cyber-physical infrastructures, yet a comprehensive review focusing on mathematical modeling and different optimization methods is still lacking. Thus, this review paper appraises the literature on optimization techniques for CPS facing disruption, to synthesize key findings on the current methods in this domain. A total of 108 relevant research papers are reviewed following an extensive assessment of all major scientific databases. The main mathematical modeling practices and optimization methods are identified for both deterministic and stochastic formulations, categorizing them based on the solution approach (exact, heuristic, meta-heuristic), objective function, and network size. We also perform keyword clustering and bibliographic coupling analyses to summarize the current research trends. Future research needs in terms of the scalability of optimization algorithms are discussed. Overall, there is a need to shift towards more scalable optimization solution algorithms, empowered by data-driven methods and machine learning, to provide reliable decision-support systems for decision-makers and practitioners

Food Risks and Type I & II Errors

The IFAMR is published by (IFAMA) the International Food and Agribusiness Management Review. www.ifama.orgFood safety, food defense, error based disruption, control oriented supply networks, Agribusiness, Food Consumption/Nutrition/Food Safety, Food Security and Poverty, Risk and Uncertainty, Q130,

Transportation, Terrorism and Crime: Deterrence, Disruption and Resilience

Abstract: Terrorists likely have adopted vehicle ramming as a tactic because it can be carried out by an individual (or “lone wolf terrorist”), and because the skills required are minimal (e.g. the ability to drive a car and determine locations for creating maximum carnage). Studies of terrorist activities against transportation assets have been conducted to help law enforcement agencies prepare their communities, create mitigation measures, conduct effective surveillance and respond quickly to attacks. This study reviews current research on terrorist tactics against transportation assets, with an emphasis on vehicle ramming attacks. It evaluates some of the current attack strategies, and the possible mitigation or response tactics that may be effective in deterring attacks or saving lives in the event of an attack. It includes case studies that can be used as educational tools for understanding terrorist methodologies, as well as ordinary emergencies that might become a terrorist’s blueprint

Responsive Contingency Planning for Supply Chain Disruption Risk Mitigation

Contingent sourcing from a backup resource is an effective risk mitigation strategy under major disruptions. The production volumes and speeds of the backup resource are important protection design considerations, as they affect recovery. The objective of this dissertation is to show that cost-effective protection of existing supply networks from major disruptions result from planning appropriate volume and response speeds of a backup production facility prior to the disruptive event by considering operational aspects such as congestion that may occur at facilities. Contingency strategy are more responsive and disruption recovery periods can be shortened through such prior planning. The dissertation focuses on disruption risk arising from intelligent or pre-meditated attacks on supply facilities. An intelligent attacker has the capability to create worst case loss depending on the protection strategy of a given network. Since the attacker seeks the maximum loss and the designer tries to identify the protection scheme which minimizes this maximum loss, there exists an interdependence between attack and protection decisions. Ignoring this characteristic leads to suboptimal mitigation solutions under such disruptions. We therefore develop a mathematical model which utilizes a game theoretic framework of attack and defense involving nested optimization problems. The model is used to decide optimal selection of backup production volume and the response speeds, the facilities to build such capability within the available budget. The reallocation of demands from a disrupted facility to an undisrupted facility in a contingency strategy leads to congestion of the undisrupted facility, which may result in longer lead times and reduced throughput during disruption periods, thereby limiting the effectiveness of a contingency strategy. In the second part of the dissertation, we therefore analyze congestion effects in responsive contingency planning. The congestion cost function is modeled and integrated into the mathematical model of responsive contingency planning developed in the first part of the dissertation. The main contribution of this dissertation is that a decision tool has been developed to plan protection of an existing supply networks considering backup sourcing through gradual capacity acquisition. The solution methodology involving recursive search tree has been implemented which allows exploring protection solutions under a given budget of protection and multiple combinations of response speeds and production capacities of a backup facility. The results and analysis demonstrate the value of planning for responsive contingency in supply chains subject to risks of major disruptions and provide insights to aid managerial decision making

Ready or Not? Protecting the Public's Health From Diseases, Disasters, and Bioterrorism, 2011

Highlights examples of preparedness programs and capacities at risk of federal budget cuts or elimination, examines state and local public health budget cuts, reviews ten years of progress and shortfalls, and outlines policy issues and recommendations

Disentangling the resiliency of international transportation systems under uncertainty by a novel multi-layer spherical fuzzy decision-making framework:Evidence from an emerging economy

Although transportation systems play a critical role in the global socio-economic facets, they are acknowledged as vulnerable systems directly impacted by unexpected events, e.g., natural calamities, war, traffic accidents, terrorist attacks, and public health. In this respect, improving the resiliency of transportation systems under uncertainty is a controversial global challenge that this study could underpin. To do so, a systematic literature review (SLR) extracted a list of resiliency factors for resilient transportation systems. Next, a novel version of spherical fuzzy Delphi (SFD) screened factors, considering the case of Iran’s international maritime transportation system. Moreover, the causal network relationship of the finalised factors was analysed by a novel hybrid spherical fuzzy approach, including a decision-making trial and evaluation laboratory (DEMATEL) and the analytic network process (ANP). Later, the unexpected events that occurred after 2000 were investigated. The SLR deeply investigated 51 of the top relevant articles. As a result, 12 factors and 22 subfactors that affect transportation systems resiliency were extracted. Notably, the rest of the findings primarily apply to the Iranian context. By implementing the SFD, ten factors were screened for Iran’s international maritime transportation system and then analysed by SF-DEMATEL. After, the analysed factors were weighted by SFANP, where “recoverability” was selected as the most critical factor, and the “technological and communicational” factor was chosen as the least critical factor. Furthermore, the results provide a critical analysis of the policies adopted by Iran’s international maritime transportation system to enhance resiliency under disruptive events

Disentangling the resiliency of international transportation systems under uncertainty by a novel multi-layer spherical fuzzy decision-making framework:Evidence from an emerging economy

Although transportation systems play a critical role in the global socio-economic facets, they are acknowledged as vulnerable systems directly impacted by unexpected events, e.g., natural calamities, war, traffic accidents, terrorist attacks, and public health. In this respect, improving the resiliency of transportation systems under uncertainty is a controversial global challenge that this study could underpin. To do so, a systematic literature review (SLR) extracted a list of resiliency factors for resilient transportation systems. Next, a novel version of spherical fuzzy Delphi (SFD) screened factors, considering the case of Iran’s international maritime transportation system. Moreover, the causal network relationship of the finalised factors was analysed by a novel hybrid spherical fuzzy approach, including a decision-making trial and evaluation laboratory (DEMATEL) and the analytic network process (ANP). Later, the unexpected events that occurred after 2000 were investigated. The SLR deeply investigated 51 of the top relevant articles. As a result, 12 factors and 22 subfactors that affect transportation systems resiliency were extracted. Notably, the rest of the findings primarily apply to the Iranian context. By implementing the SFD, ten factors were screened for Iran’s international maritime transportation system and then analysed by SF-DEMATEL. After, the analysed factors were weighted by SFANP, where “recoverability” was selected as the most critical factor, and the “technological and communicational” factor was chosen as the least critical factor. Furthermore, the results provide a critical analysis of the policies adopted by Iran’s international maritime transportation system to enhance resiliency under disruptive events

Report of the Working Group on Government Securities Clearance and Settlement

Terrorism ; Financial markets

Sustainability Assessment of Community Scale Integrated Energy Systems: Conceptual Framework and Applications

abstract: One of the key infrastructures of any community or facility is the energy system which consists of utility power plants, distributed generation technologies, and building heating and cooling systems. In general, there are two dimensions to “sustainability” as it applies to an engineered system. It needs to be designed, operated, and managed such that its environmental impacts and costs are minimal (energy efficient design and operation), and also be designed and configured in a way that it is resilient in confronting disruptions posed by natural, manmade, or random events. In this regard, development of quantitative sustainability metrics in support of decision-making relevant to design, future growth planning, and day-to-day operation of such systems would be of great value. In this study, a pragmatic performance-based sustainability assessment framework and quantitative indices are developed towards this end whereby sustainability goals and concepts can be translated and integrated into engineering practices. New quantitative sustainability indices are proposed to capture the energy system environmental impacts, economic performance, and resilience attributes, characterized by normalized environmental/health externalities, energy costs, and penalty costs respectively. A comprehensive Life Cycle Assessment is proposed which includes externalities due to emissions from different supply and demand-side energy systems specific to the regional power generation energy portfolio mix. An approach based on external costs, i.e. the monetized health and environmental impacts, was used to quantify adverse consequences associated with different energy system components. Further, this thesis also proposes a new performance-based method for characterizing and assessing resilience of multi-functional demand-side engineered systems. Through modeling of system response to potential internal and external failures during different operational temporal periods reflective of diurnal variation in loads and services, the proposed methodology quantifies resilience of the system based on imposed penalty costs to the system stakeholders due to undelivered or interrupted services and/or non-optimal system performance. A conceptual diagram called “Sustainability Compass” is also proposed which facilitates communicating the assessment results and allow better decision-analysis through illustration of different system attributes and trade-offs between different alternatives. The proposed methodologies have been illustrated using end-use monitored data for whole year operation of a university campus energy system.Dissertation/ThesisDoctoral Dissertation Civil, Environmental and Sustainable Engineering 201

STRATEGIC DECISION MAKING IN SUPPLY CHAINS UNDER RISK OF DISRUPTIONS

Ph.DDOCTOR OF PHILOSOPH