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Collaborative plan execution is becoming increasingly important given its potential for operational agility and cost reduction. In this paper we propose a distributed and hierarchy aware monitoring procedure for operational plan execution taking place in a dynamic environment characterized by unreliable communication and exogenous events. The contribution of this paper consists in employing a hierarchical clustering approach supporting a multi-party and hierarchy aware information sharing mechanism that is resilient to disruptions in the execution environment. The proposed distributed monitoring procedure uses asymmetric clustering to reflect hierarchical relationships along with gossip based communication across the clusters. Of significance is the information sharing mechanism formalization which utilizes a fresh information window in conjunction with communicating Markov Decision Processes. We show the usefulness of assessing shared information awareness via probabilistic model checking for various combinations of clustering topology and disruption conditions. In this context, we assess formal specifications expressed in probabilistic temporal logic and show how the model checking results can be used to derive the best fresh window value to maximize an information awareness utility function. An illustrative case study is also presented. [ABSTRACT FROM AUTHOR]

Transportation and supply chain activities represent essential components in many endeavors covering both public and private domains. However, the underlying transport networks are complex and potentially fragile due to weather, natural disasters or other risk factors. Thus, assessing transportation related risk represents a key decision support capability along with the ability to evaluate contingency options for risk mitigation. In this paper, we address these issues by adopting probabilistic model checking to evaluate the risk and contingency options related to transportation tasks. In this pursuit, risk related properties are assessed for behavioral models capturing the transport system. Moreover, we show the usefulness of constructing decision trees that can provide insightful means of risk appraisal. The proposed approach can help decision makers evaluate contingency options and determine lower and upper cost bounds for risky transportation tasks such as those involved in humanitarian aid provision. The proposed approach is also illustrated with a case study. [ABSTRACT FROM AUTHOR]

Facility location problems (FLP) are often solved as uncapacitated facility location (UFL) instances. Also, typical solution approaches in the literature assume that the established facilities are totally reliable. However, in practice, facilities have limited capacity and can be under risk of partial disruptions whereby their failure leads to a notably higher cost. In this context, this paper presents a novel integer programming formulation for the capacitated FLP under disruption, namely the reliable capacitated facility location (RCFL) problem. The latter considers heterogeneous facility failure probabilities, one layer of backup for supply locations, limited supply capacity and facility fortification within a limited budget to mitigate failure risk. The proposed solution approach involves a linearization of the proposed model and an iterative approach for the fortification budget allocation in conjunction with the CPLEX solver. Moreover, a relevant case study is used to illustrate the approach and benchmark result are also provided. [ABSTRACT FROM AUTHOR]

In practice, the execution of plans with vehicle routing components is often subjected to external events since the transporting vehicles can be exposed to various risk factors. This may lead to delivery failure, vehicle breakdown, commodity loses, etc. In this setting, the stakeholders can benefit from logistic planning techniques whereby potential vehicle breakdown and cargo delivery failure can be mitigated by limiting vehicle risk exposure and prioritizing deliveries of larger payloads. In this paper, we propose a cost effective learning-based heuristic technique to minimize the routing cost along with the potential cost due to the risk of vehicle breakdown and cargo delivery failure. The approach is elaborated by means of an illustrative case study, and it is accompanied by benchmark results along with a comparative study. The heuristic solution generation approach can be used to mitigate vehicle routing risk at the planning stage as well as during various proactive and reactive plan adaptation activities in response to the occurrence of exogenous events. [ABSTRACT FROM AUTHOR]

Highlights • Investigation of two reliable facility location problems under disruption. • Elaboration of an evolutionary learning based solution generation approach. • Application of the approach over an illustrative example and benchmark datasets. • Comparative analysis and benefit assessment against previously obtained results. • Sensitivity analysis on demand priority and different distance calculation methods. Abstract Facility location represents an important supply chain problem aiming at minimizing facility establishment and transportation cost to meet customer demands. Many facility location problem (FLP) instances can be modelled as p -median problems (PMP) and uncapacitated facility location (UFL) problems. While, most solution approaches assume totally reliable deployed facilities, facilities often experience disruptions and their failure often leads to a notably higher cost. Therefore, determination of facility locations and fortification of a subset of them within a limited budget are crucial to supply chain organizations to provide cost effective services in presence of probable disruptions. We propose an evolutionary learning technique to near-optimally solve two research problems: Reliable p -Median Problem and Reliable Uncapacitated Facility Location Problem considering heterogeneous facility failure probabilities, one layer of backup and limited facility fortification budget. The technique is illustrated using a case study and its performance is evaluated via benchmark results. We also provide an analysis on the effects on facility location by prioritizing customer demands and adopting geographic distance calculation. The approach allows fast generation of cost-effective and complete solution using reasonable computing power. Moreover, the underlying technique is customizable offering a trade-off between solution quality and computation time. [ABSTRACT FROM AUTHOR]

In this paper, we propose an auxiliary two-layer blockchain framework to improve the security and reliability of Wide Area Measurement Systems (WAMS) in smart grids against adverse manipulation of time synchronization and interference with fault identification. The framework benefits from the blockchain's inherent advantages, such as distributed storage, consensus mechanism, and avoidance of single-point of failure while addressing typical challenges of employing blockchain technology in smart grids, such as the limitation of computation power and the high bandwidth requirements for data exchange. In the first layer of the proposed architecture, the security state of the system is determined based on the state opinion of Phasor Measurement Units (PMUs), using a consensus mechanism. Then, in the second layer, Phasor Data Concentrators (PDCs) use the first layer opinion to preserve the proper WAMS operation when some of the PMUs are compromised. In this setting and by utilizing a co-simulation testbed, we show the effectiveness of using smart contracts whereby PMUs and PDCs can reliably communicate and aggregate smart grid measurements while time synchronization and fault identification functionalities are appropriately maintained. We also evaluate several deployment scenarios and provide corresponding recommendations for the security enhancement of WAMS. Finally, we detail a fortification strategy that the Power System Operator (PSO) can use to harden the blockchain network, based on an adversarial model. • A two-layer blockchain on top of WAMS to securely store data in a distributed ledger. • Taking consensus in two steps for data of voltage measurement and time stamps. • Assessing the security for attacks on time synchronization and fault identification. • Evaluating several deployments and recommendations for enhancing WAMS security. [ABSTRACT FROM AUTHOR]