Differentiated consensuses in a stochastic network with priorities,”

Abstract-In this paper a distributed stochastic network system with incoming tasks that are classified with priorities is studied. The network system is assumed to have variable topology, and agents are not necessarily always connected to each other. In addition, the observations about neighbors' states are supposed to be obtained with random noise and delays. To ensure efficient operation of this network system, a novel control strategy is proposed. With this strategy, network resources are allocated in a randomized way with probabilities corresponding to each priority class. To maintain the balanced load across the network for different priorities, a so-called "differentiated consensuses" problem is examined. This consensus problem is that, in a system with multiple classes, consensus is targeted for each class, which may be different among classes. In this paper, the ability of the proposed control protocol to maintain almost balanced load, i.e. approximate consensus for every priority class across the network, is proved. In addition, a numerical example that illustrates the proposed control strategy and the results of simulations are provided

Advances in Computational Social Science and Social Simulation

Aquesta conferència és la celebració conjunta de la "10th Artificial Economics Conference AE", la "10th Conference of the European Social Simulation Association ESSA" i la "1st Simulating the Past to Understand Human History SPUHH".Conferència organitzada pel Laboratory for Socio­-Historical Dynamics Simulation (LSDS-­UAB) de la Universitat Autònoma de Barcelona.Readers will find results of recent research on computational social science and social simulation economics, management, sociology,and history written by leading experts in the field. SOCIAL SIMULATION (former ESSA) conferences constitute annual events which serve as an international platform for the exchange of ideas and discussion of cutting edge research in the field of social simulations, both from the theoretical as well as applied perspective, and the 2014 edition benefits from the cross-fertilization of three different research communities into one single event. The volume consists of 122 articles, corresponding to most of the contributions to the conferences, in three different formats: short abstracts (presentation of work-in-progress research), posters (presentation of models and results), and full papers (presentation of social simulation research including results and discussion). The compilation is completed with indexing lists to help finding articles by title, author and thematic content. We are convinced that this book will serve interested readers as a useful compendium which presents in a nutshell the most recent advances at the frontiers of computational social sciences and social simulation researc

Fuelling the zero-emissions road freight of the future: routing of mobile fuellers

The future of zero-emissions road freight is closely tied to the sufficient availability of new and clean fuel options such as electricity and Hydrogen. In goods distribution using Electric Commercial Vehicles (ECVs) and Hydrogen Fuel Cell Vehicles (HFCVs) a major challenge in the transition period would pertain to their limited autonomy and scarce and unevenly distributed refuelling stations. One viable solution to facilitate and speed up the adoption of ECVs/HFCVs by logistics, however, is to get the fuel to the point where it is needed (instead of diverting the route of delivery vehicles to refuelling stations) using "Mobile Fuellers (MFs)". These are mobile battery swapping/recharging vans or mobile Hydrogen fuellers that can travel to a running ECV/HFCV to provide the fuel they require to complete their delivery routes at a rendezvous time and space. In this presentation, new vehicle routing models will be presented for a third party company that provides MF services. In the proposed problem variant, the MF provider company receives routing plans of multiple customer companies and has to design routes for a fleet of capacitated MFs that have to synchronise their routes with the running vehicles to deliver the required amount of fuel on-the-fly. This presentation will discuss and compare several mathematical models based on different business models and collaborative logistics scenarios

Risk in Sports and Challenges for Sports Organizations

Success, injuries, future career opportunities of athletes, and the societal gains of participating in sports and organizing (mega) sports events are all related to individual risk-taking behavior. Although the sports economics and management literature has broadly addressed these issues, it is surprising that less attention has been paid to the implications of risk-taking on the organization of sports in general and, more particularly, on the design and behavior of sports organization members

Risk in Sports and Challenges for Sports Organizations

Success, injuries, future career opportunities of athletes, and the societal gains of participating in sports and organizing (mega) sports events are all related to individual risk-taking behavior. Although the sports economics and management literature has broadly addressed these issues, it is surprising that less attention has been paid to the implications of risk-taking on the organization of sports in general and, more particularly, on the design and behavior of sports organization members

An empirical investigation in the decision-making processes of new infrastructure development

The aim of this research is to present and discuss the development and deployment of Lean thinking models and techniques applied to improve the decision-making within the planning and design processes of new infrastructures, within a healthcare organisation. In the UK, healthcare organisations are responsible for planning, designing, building and managing their own infrastructures, through which their services are delivered to the local population (Kagioglou & Tzortzopoulos, 2010). These processes are long and complex, involving a large range of stakeholders who are implicated within the strategic decision-making. It is understood that the NHS lacks models and frameworks to support the decision-making associated with their new infrastructure development and that ad-hoc methods, used at local level, lead to inefficiencies and weak performances, despite the contractual efforts made throughout the PPP and PFI schemes (Baker & Mahmood, 2012; Barlow & Koberle-Gaiser, 2008). This is illustrated by the long development cycle time – it can take up to 15 years from conception to completion of new infrastructure. Hence, in collaboration with an NHS organisation, an empirical action research embedded within a mixed-methodology approach, has been designed to analyse the root-cause problems and assess to what extent Lean thinking can be applied to the built environment, to improve the speed and fitness for purpose of new infrastructures. Firstly, this multiphase research establishes the main issues responsible for the weak process performances, via an inductive-deductive cycle, and then demonstrates how Lean thinking inspired techniques: Multiple Criteria Decision Analysis (MCDA) using ER and AHP, Benchmarking and Quality Function Deployment (QFD), have been implemented to optimise the decision-making in order to speed up the planning and design decision-making processes and to enhance the fitness for purpose of new infrastructures. Academic literatures on Lean thinking, decision theories and built environment have been reviewed, in order to establish a reliable knowledge base of the context and to develop relevant solutions. The bespoke models developed have been tested and implemented in collaboration with a local healthcare organisation in UK, as part of the construction of a £15 million health centre project. A substantial set of qualitative and quantitative data has been collected during the 450 days, which the researcher was granted full access, plus a total of 25 sets of interviews, a survey (N=85) and 25 experimental workshops. This mixed-methodology research is composed of an exploratory sequential design and an embedded-experiment variant, enabling the triangulation of different data, methods and findings to be used to develop an innovative solution, thus improving the new infrastructure development process. The emerging developed conceptual model represents a non-prescriptive approach to planning and designing new healthcare infrastructures, using Lean thinking principles to optimise the decision-making and reduce the complexity. This Partial & Bespoke Lean Construction Framework (PBLCF) has been implemented as good practice by the healthcare organisation, to speed up the planning phases and to enhance the quality of the design and reduce the development cost, in order to generate a competitive edge. It is estimated that a reduction of 22% of the cycle time and 7% of the cost is achievable. This research makes a contribution by empirically developing and deploying a partial Lean implementation into the healthcare‟s built environment, and by providing non-prescriptive models to optimise the decision-making underpinning the planning and design of complex healthcare infrastructure. This has the potential to be replicated in other healthcare organisations and can also be adapted to other construction projects