A Hybrid Queue-based Bayesian Network framework for passenger facilitation modelling

This paper presents a novel framework for the modelling of passenger facilitation in a complex environment. The research is motivated by the challenges in the airport complex system, where there are multiple stakeholders, differing operational objectives and complex interactions and interdependencies between different parts of the airport system. Traditional methods for airport terminal modelling do not explicitly address the need for understanding causal relationships in a dynamic environment. Additionally, existing Bayesian Network (BN) models, which provide a means for capturing causal relationships, only present a static snapshot of a system. A method to integrate a BN complex systems model with stochastic queuing theory is developed based on the properties of the Poisson and exponential distributions. The resultant Hybrid Queue-based Bayesian Network (HQBN) framework enables the simulation of arbitrary factors, their relationships, and their effects on passenger flow and vice versa. A case study implementation of the framework is demonstrated on the inbound passenger facilitation process at Brisbane International Airport. The predicted outputs of the model, in terms of cumulative passenger flow at intermediary and end points in the inbound process, are found to have an R2 goodness of fit of 0.9994 and 0.9982 respectively over a 10 h test period. The utility of the framework is demonstrated on a number of usage scenarios including causal analysis and ‘what-if’ analysis. This framework provides the ability to analyse and simulate a dynamic complex system, and can be applied to other socio-technical systems such as hospitals.

Innovate triple constraints model for better construction projects results

The continuous changing impacts appeared in all solution understanding approaches in the projects management field (especially in the construction field of work) by adopting dynamic solution paths. The paper will define what argue to be a better relational model for project management constraints (time, cost, and scope). This new model will increase the success factors of any complex program / project. This is a qualitative research adopting a new avenue of investigation by following different approach of attributing project activities with social phenomena, and supporting phenomenon with field of observations rather than mathematical method by emerging solution from human, and ants' colonies successful practices. The results will show the correct approach of relation between the triple constraints considering the relation as multi agents system having specified communication channels based on agents locations. Information will be transferred between agents, and action would be taken based on constraint agents locations in the project structure allowing immediate changes abilities in order to overcome issues of over budget, behind schedule, and additional scope impact. This is complex adaptive system having self organizes technique, and cybernetic control. Resulted model can be used for improving existing project management methodologies.

Dynamic agent composition for large-scale agent-based models

PURPOSE: This paper describes dynamic agent composition, used to support the development of flexible and extensible large-scale agent-based models (ABMs). This approach was motivated by a need to extend and modify, with ease, an ABM with an underlying networked structure as more information becomes available. Flexibility was also sought after so that simulations are set up with ease, without the need to program. METHODS: The dynamic agent composition approach consists in having agents, whose implementation has been broken into atomic units, come together at runtime to form the complex system representation on which simulations are run. These components capture information at a fine level of detail and provide a vast range of combinations and options for a modeller to create ABMs. RESULTS: A description of the dynamic agent composition is given in this paper, as well as details about its implementation within MODAM (MODular Agent-based Model), a software framework which is applied to the planning of the electricity distribution network. Illustrations of the implementation of the dynamic agent composition are consequently given for that domain throughout the paper. It is however expected that this approach will be beneficial to other problem domains, especially those with a networked structure, such as water or gas networks. CONCLUSIONS: Dynamic agent composition has many advantages over the way agent-based models are traditionally built for the users, the developers, as well as for agent-based modelling as a scientific approach. Developers can extend the model without the need to access or modify previously written code; they can develop groups of entities independently and add them to those already defined to extend the model. Users can mix-and-match already implemented components to form large-scales ABMs, allowing them to quickly setup simulations and easily compare scenarios without the need to program. The dynamic agent composition provides a natural simulation space over which ABMs of networked structures are represented, facilitating their implementation; and verification and validation of models is facilitated by quickly setting up alternative simulations.

An agent-based approach to immune modelling

This study focuses on trying to understand why the range of experience with respect to HIV infection is so diverse, especially as regards to the latency period. The challenge is to determine what assumptions can be made about the nature of the experience of antigenic invasion and diversity that can be modelled, tested and argued plausibly. To investigate this, an agent-based approach is used to extract high-level behaviour which cannot be described analytically from the set of interaction rules at the cellular level. A prototype model encompasses local variation in baseline properties contributing to the individual disease experience and is included in a network which mimics the chain of lymphatic nodes. Dealing with massively multi-agent systems requires major computational efforts. However, parallelisation methods are a natural consequence and advantage of the multi-agent approach. These are implemented using the MPI library.

Systems modelling of the socio-technical aspects of residential electricity use and network peak demand

Provision of network infrastructure to meet rising network peak demand is increasing the cost of electricity. Addressing this demand is a major imperative for Australian electricity agencies. The network peak demand model reported in this paper provides a quantified decision support tool and a means of understanding the key influences and impacts on network peak demand. An investigation of the system factors impacting residential consumers’ peak demand for electricity was undertaken in Queensland, Australia. Technical factors, such as the customers’ location, housing construction and appliances, were combined with social factors, such as household demographics, culture, trust and knowledge, and Change Management Options (CMOs) such as tariffs, price,managed supply, etc., in a conceptual ‘map’ of the system. A Bayesian network was used to quantify the model and provide insights into the major influential factors and their interactions. The model was also used to examine the reduction in network peak demand with different market-based and government interventions in various customer locations of interest and investigate the relative importance of instituting programs that build trust and knowledge through well designed customer-industry engagement activities. The Bayesian network was implemented via a spreadsheet with a tick box interface. The model combined available data from industry-specific and public sources with relevant expert opinion. The results revealed that the most effective intervention strategies involve combining particular CMOs with associated education and engagement activities. The model demonstrated the importance of designing interventions that take into account the interactions of the various elements of the socio-technical system. The options that provided the greatest impact on peak demand were Off-Peak Tariffs and Managed Supply and increases in the price of electricity. The impact in peak demand reduction differed for each of the locations and highlighted that household numbers, demographics as well as the different climates were significant factors. It presented possible network peak demand reductions which would delay any upgrade of networks, resulting in savings for Queensland utilities and ultimately for households. The use of this systems approach using Bayesian networks to assist the management of peak demand in different modelled locations in Queensland provided insights about the most important elements in the system and the intervention strategies that could be tailored to the targeted customer segments.

A near Optimal Cane Rail Scheduler under Limited and Unlimited Capacity Constraints

Australia is the world’s third largest exporter of raw sugar after Brazil and Thailand, with around $2.0 billion in export earnings. Transport systems play a vital role in the raw sugar production process by transporting the sugarcane crop between farms and mills. In 2013, 87 per cent of sugarcane was transported to mills by cane railway. The total cost of sugarcane transport operations is very high. Over 35% of the total cost of sugarcane production in Australia is incurred in cane transport. A cane railway network mainly involves single track sections and multiple track sections used as passing loops or sidings. The cane railway system performs two main tasks: delivering empty bins from the mill to the sidings for filling by harvesters; and collecting the full bins of cane from the sidings and transporting them to the mill. A typical locomotive run involves an empty train (locomotive and empty bins) departing from the mill, traversing some track sections and delivering bins at specified sidings. The locomotive then, returns to the mill, traversing the same track sections in reverse order, collecting full bins along the way. In practice, a single track section can be occupied by only one train at a time, while more than one train can use a passing loop (parallel sections) at a time. The sugarcane transport system is a complex system that includes a large number of variables and elements. These elements work together to achieve the main system objectives of satisfying both mill and harvester requirements and improving the efficiency of the system in terms of low overall costs. These costs include delay, congestion, operating and maintenance costs. An effective cane rail scheduler will assist the traffic officers at the mill to keep a continuous supply of empty bins to harvesters and full bins to the mill with a minimum cost. This paper addresses the cane rail scheduling problem under rail siding capacity constraints where limited and unlimited siding capacities were investigated with different numbers of trains and different train speeds. The total operating time as a function of the number of trains, train shifts and a limited number of cane bins have been calculated for the different siding capacity constraints. A mathematical programming approach has been used to develop a new scheduler for the cane rail transport system under limited and unlimited constraints. The new scheduler aims to reduce the total costs associated with the cane rail transport system that are a function of the number of bins and total operating costs. The proposed metaheuristic techniques have been used to find near optimal solutions of the cane rail scheduling problem and provide different possible solutions to avoid being stuck in local optima. A numerical investigation and sensitivity analysis study is presented to demonstrate that high quality solutions for large scale cane rail scheduling problems are obtainable in a reasonable time. Keywords: Cane railway, mathematical programming, capacity, metaheuristics

Enhancing skill acquisition and expertise in high performance programmes

Our research programme with elite athletes has investigated and implemented learning design from an ecological dynamics perspective, examining its effects on movement coordination and control and the acquisition of expertise. Ecological dynamics is a systemsoriented theoretical rationale for understanding the emergent relations in a complex system formed by each performer and a performance environment. This approach has identified the individual-environment relationship as the relevant scale of analysis for modelling how processes of perception, cognition and action underpin expert performance in sport (Davids et al., 2014; Zelaznik, 2014). In this chapter we elucidate key concepts from ecological dynamics and exemplify how they have informed our understanding of relevant psychological processes including: movement coordination and its acquisition, learning and transfer, impacting on practice task design in high performance programmes.

Is Habermas on Twitter? Social Media and the Public Sphere

Jürgen Habermas’s concept of the public sphere remains a major building block for our understanding of public communication and deliberation. Yet ‘the’ public sphere is a construct of its time, and the mass media-dominated environment which it describes has given way to a considerably more fragmented and complex system of distinct and diverse, yet interconnected and overlapping publics that represent different themes, topics, and approaches to mediated communication. This chapter argues that moving beyond the orthodox model of the public sphere to a more dynamic and complex conceptual framework provides the opportunity to more clearly recognise the varying forms that public communication can take, especially online. Unpacking the traditional public sphere into a series of public sphericules and micro-publics, none of which are mutually exclusive but which co-exist, intersecting and overlapping in multiple forms, is crucial for understanding the ongoing structural transformation of ‘the’ public sphere.

Influencing customers through customers: Simulation of herd behavior in supermarkets

This work proposes a supermarket optimization simulation model called Swarm-Moves is based on self organized complex system studies to identify parameters and their values that can influence customers to buy more on impulse in a given period of time. In the proposed model, customers are assumed to have trolleys equipped with technology like RFID that can aid the passing of products' information directly from the store to them in real-time and vice-versa. Therefore, they can get the information about other customers purchase patterns and constantly informing the store of their own shopping behavior. This can be easily achieved because the trolleys "know" what products they contain at any point. The Swarm-Moves simulation is the virtual supermarket providing the visual display to run and test the proposed model. The simulation is also flexible to incorporate any given model of customers' behavior tailored to particular supermarket, settings, events or promotions. The results, although preliminary, are promising to use RFID technology for marketing products in supermarkets and provide several dimensions to look for influencing customers via feedback, real-time marketing, target advertisement and on-demand promotions. ©2009 IEEE.

Charting the system : the integrated master schedule as a multi-level and poly-temporal boundary object in complex projects

This paper investigates the use of visual artifacts to represent a complex adaptive system (CAS). The integrated master schedule (IMS) is one of those visuals widely used in complex projects for scheduling, budgeting, and project management. In this paper, we discuss how the IMS outperforms the traditional timelines and acts as a ‘multi-level and poly-temporal boundary object’ that visually represents the CAS. We report the findings of a case study project on the way the IMS mapped interactions, interdependencies, constraints and fractal patterns in a complex project. Finally, we discuss how the IMS was utilised as a complex boundary object by eliciting commitment and development of shared mental models, and facilitating negotiation through the layers of multiple interpretations from stakeholders.

Understanding IT value : a multilevel, complex, and adaptive system perspective

One remaining difficulty in the Information Technology (IT) business value evaluation domain is the direct linkage between IT value and the underlying determinants of IT value or surrogates of IT value. This paper proposes a research that examines the interacting effects of the determinants of IT value, and their influences on IT value. The overarching research question is how those determinants interact with each other and affect the IT value at organizational value. To achieve this, this research embraces a multilevel, complex, and adaptive system view, where the IT value emerges from the interacting of underlying determinants. This research is theoretically grounded on three organizational theories – multilevel theory, complex adaptive systems theory, and adaptive structuration theory. By integrating those theoretical paradigms, this research proposes a conceptual model that focuses on the process where IT value is created from interactions of those determinants. To answer the research question, agent-based modeling technique is used in this research to build a computational representation based on the conceptual model. Computational experimentation will be conducted based on the computational representation. Validation procedures will be applied to consolidate the validity of this model. In the end, hypotheses will be tested using computational experimentation data.

Guanxi as complex adaptive system : definition, description and underlying principles

Guanxi has become a common term in the wider business community and has attracted an increasing attention of researchers. However, a consistent understanding of the concept continues to be elusive. We critically review the extant guanxi literature to identify the major inconsistencies in the way guanxi is currently conceptualized and develop a conceptualization of guanxi which views guanxi as a complex adaptive system formed by the strategic establishing, evolving, utilizing, and maintaining of personal relationships based upon social norms of trust and reciprocal obligation unique to the Chinese culture. This study contributes to research of guanxi and to the field of Chinese management in several ways. First, we identify four levels of inconsistency surrounding the conceptualization of guanxi in the literature, thus clarifying the current common sources of confusion. Second, this study deconstructs the level and core values of guanxi to provide a more transparent picture, enabling researchers to develop more robust measures of guanxi. Finally, we made progress towards a more comprehensive understanding of guanxi by introducing the complex adaptive system perspective into the guanxi research.