International Journal of Simulation and Process Modelling (21 papers in press)
Stability-based model for evacuation system using agent-based social simulation and Monte Carlo method
by Makhlouf Naili, Mustapha Bourahla, Mohamed Naili
Abstract: The agent-based modelling is used for modelling many complex dynamic systems, especially those including autonomous individuals, such as human beings' societies, animal societies, robots, insect societies, etc. Evacuation systems such as those needed for supermarket buildings are considered as complex dynamic systems. In these systems, we have to deal with the problem of rescuing a high number of people of different ages, sex, physical characteristics, etc. Furthermore, this process mostly runs in buildings with different constraints such as locations of the rows of shelves, exit gates, etc. On one hand, in order to deal with disasters such as fire propagation, studying this kind of system using a dynamic model has a great importance in order to avoid the maximum of casualties. On the other hand, the model that represents this kind of system must take into account several factors, such as time, the buildings characteristics and peoples characteristics. In this study, an agent-based model has been designed to visualise the dynamic system behaviour via these internal entities that often interact. Additionally, we use some dynamic data mining methods such as Monte Carlo method to calculate the stable characteristics of this model via a probabilistic approach.
Keywords: agent-based modelling; dynamic data mining; dynamic models; evacuation building system; Monte Carlo simulation; stability; steady state.
Swarm intelligent algorithm For re-entrant hybrid flow shop Scheduling Problems
by Zhonghua Han, Xutian Tian, Xiaoting Dong, Fanyi Xie
Abstract: In order to solve the Re-entrant Hybrid Flowshop (RHFS) scheduling problems and establish mathematics scheduling models, this paper uses Wolf Pack Algorithm (WPA) as the global optimisation. For local assignment, it takes maximum residential time-oriented rule. Scouting behaviours of wolves are changed in the former optimisation by means of levy flight, extending searching ranges and increasing the rapidity of convergence. When it comes to local extremum of wolves, the individual with high similarity of dynamic changes adds diversity. Hanming distance is used to judge individual similarity for increased quality of new one, strong algorithm ability and energetic revolution. A painting workshop in a bus manufacture enterprise have some typical features of re-entrant hybrid flowshop. Regarding it as the algorithm applied target, this paper focus on resolving this problem with WPA and various advanced algorithms. The results show that advanced algorithms can solve re-entrant hybrid flowshop scheduling problems effectively.
Keywords: re-entrant hybrid flow shop; mathematics scheduling models; Hanming distance; levy flight; swarm intelligent algorithm.
The structure optimisation of hydraulic mechanical screw pump
by Zhenfu Ma
Abstract: In the current stage of oilfield development, the screw pump is an advanced mechanical oil recovery process. In the process of lifting oil and other liquids in the well, the screw pump has good and stable characteristics of pumping force under high pressure This paper takes Shengli Oilfield water flooding development as the engineering background, aiming at the problem that the flow ratio of the screw motor and the screw pump affects the efficiency. The changing rules of influencing factors, such as luffing coefficient and eccentric coefficient, over the flow area, and the relative sliding velocity are modelled and analysed. With the amplitude coefficient and eccentric coefficient as decision variables, the equatorial short hypochromic curve is optimised to get the best ratio of each head of the parameters and end line type.
Keywords: screw pump; screw motor; luffing coefficient; eccentricity coefficient; optimisation.
Cogent: a coherence-driven cognitive agent modelling and experimentation framework
by Sunit Sivaraj, Levent Yilmaz
Abstract: Most agent modelling and simulation languages lack high-level syntactic features necessary for cognitive modelling. In this paper, we present Cogent, an interactive coherence-driven agent specification and simulation platform and demonstrate its use in ethical decision-making. The underlying strategy is based on the concept of a connectionist, interactive activation model that implements the theory of coherence. Agents in the Cogent language are specified by a Domain Specific Language (DSL). The DSL provides the syntax for specifying the decision- making strategy along with its cognitive coherence model. The framework also provides the ability to model complex hierarchical cognitive network structures. To illustrate the utility of Cogent, we explore a machine ethics case study.
Keywords: cognitive agent; coherence; ethical decision making; cognitive computing; domain-specific language.
Modelling, simulation, and resource optimisation of complex development project by fusion of multiple-domain matrix and coloured Petri nets methods
by Gordan Topic, Dragan Jevtic
Abstract: In this research, a fusion of two methods is developed as a suitable strategy and procedure for dynamic management of complex project systems: the first method of Multiple-Domain Matrix (MDM), includes modelling complex relations between resources and activities, using rearrangement of these elements to minimize feedbacks. The second method provides an insight into the project system dynamics by performing Coloured Petri Net (CPN) simulation based on the model of project system obtained by the first method. The focus is on the unique conversion of the MDM method to CPN, where the static system description of the MDM method was expanded by the capabilities of the dynamic system description of the CPN method. The objective was to evaluate an effective technique to analyse a complex project system of software development, which enables detailed planning and optimal management to shorten the production cycle of the appropriate quality with the lowest cost.
Keywords: design/dependency structure matrix; multiple-domain matrix; coloured Petri net; conversion; simulation; project management; process modelling; software development process; complex project system.
Developing an Evolution Software Architecture Framework Based on Six Dimensions
by Noureddine Gasmallah, Abdelkrim Amirat, Mourad Oussalah, Siridi Hassina
Abstract: Because of the vital need for software systems to evolve and change over time in order to account for new requirements, software evolution at higher levels of modelling is considered as one of the main foundation within software engineering used to reduce complexity and ensure flexibility, evolvability and usability. Motivations- With the growing number of evolution methods, the need to develop a framework based on well defined dimensions to analyse these approaches, is now a prerequisite for practitioners in order to analyse, compare and classify methods within the field of architectural evolution. In similar studies for migration techniques and software engineering, presenting a framework does not usually cover the specification of systems based on software architecture subsequently, it does not give the opportunity to shape the interior design of software in terms of specific metrics. Objective- In this paper, we propose an evolution software architecture based on six dimensions for analysing, comparing and classifying existing and future evolution methods. Methods- The proposed architectural evolution framework adopts Zackman analytic tool by providing answers to What, Why, Where, Who, When and How questions. The process to formalize a framework for evolution methods relies upon identifying dimensions on which researchers would take into account while developing a new approach. The set of the proposed dimensions whether combined or individually can serve as a basis to explore further classification paradigms. Results- Six explicit dimensions are identified confirming the conceptual framework consistency in accordance with the architectural view-point of the software. The proposed framework is supported by an empirical study that involves surveying and analysing 119 research methods related to area of architectural evolution from the literature. Furthermore, these dimensions are quantified and then analysed within a case study.
Conclusion- This framework provides a blueprint to guide practitioners to position architectural evolution approaches and maps them according to a selected set of dimensions.
Keywords: Conceptual Framework; Software Architecture; Classification; Taxonomy
An interactive, interoperable and ubiquitous mixed reality application for a smart learning experience
by Francesco Longo, Letizia Nicoletti, Antonio Padovano
Abstract: This article presents an innovative comprehensive platform that includes an interactive, interoperable and ubiquitous mixed reality application that will bring beyond the way cultural digital resources are created, disseminated, preserved and re-used. As part of an extensive research effort carried out by the authors to foster the utilisation of the most recent technologies in the field of cultural heritage, this article goes further in the design and development of a prototype of an intelligent, interactive and interoperable comprehensive platform for the 21st century museums (I3-CPM). Since I3-CPM explores unconventional ways to deliver cultural contents (virtual and augmented reality, serious games, holography, simulation, knowledge based systems, vocal interaction technologies, etc.), it is expected to provide users with a new and smart learning experience. The OUTSIDE-REAL application is here described as part of the I3-CPM framework: it provides intuitive navigation of mixed reality cultural contents and storytelling through an intelligent knowledge navigator and vocal assistant, called SOPHOS, thus offering the visitors a user-driven, interactive and meaningful learning experience at the cultural heritage site.
Keywords: cultural heritage; digital museum; mixed reality; augmented reality; intelligent agents; vocal assistant; smart learning; storytelling.
Agent-based modelling and simulation of task execution and coordination in distributed organisations: the psychosocial dynamic interaction perspective
by Haibin Liu, Yufang Cheng, Qinghe Bo
Abstract: The research presents a psychosocial dynamic model of members' commitment to perform local tasks and global tasks under a distributed context. Based on theory of planned behaviour, we explore how local task self-efficacy and IT self-efficacy evolve with a computational model. The simulation results of the aerospace industry show that the organisation will emerge to a non-balanced state of development. Moreover, sites which form the distributed organisation will evolve to the independent locations in the end. For overcoming these situations, the study proposes a strategy - 'resisting foreign aggression home safe'. Moreover, a high rate of global tasks accomplishment can be achieved by improving members' IT self-efficacy, which brings in more communication and coordination between separated sites. For distributed organisations, the higher and the lower coordination are not rewarding, while the high local task self-efficacy and the moderate IT self-efficacy are beneficial.
Keywords: distributed organisations; self-efficacy; theory of planned behaviour; TPB; agent-based model; simulation.
Special Issue on: Computational Thinking and the Development of Complex Systems
Morphology-based visible-infrared image fusion framework for smart city
by Guanqiu Qi, Zhiqin Zhu, Yinong Chen, Jinchuan Wang, Qiong Zhang, Fancheng Zeng
Abstract: Sparse representation-based approaches are often applied to image fusion. Owing to the difficulties of obtaining a complete and non-redundant dictionary, this paper proposes a hierarchical image fusion framework that applies layer-by-layer deep learning techniques to explore the detailed information of images and extract key information of images for dictionary learning. According to morphological similarities, this paper clusters source image patches into smooth, stochastic, and dominant orientation patch group. High-frequency and low-frequency components of three clustered image-patch groups are fused by max-L1 and L2-norm based weighted average fusion rule respectively. The fused low-frequency and high-frequency components are combined to obtain the final fusion results. The comparison experimentations confirm the feasibility and effectiveness of the proposed image fusion solution.
Keywords: image fusion; sparse representation; dictionary learning; geometric information classification; smart city.
Three-dimensional pedestrian dead reckoning method based on gait recognition
by Min Huang, Hua-Zhao Li, Xia Wu
Abstract: With the widespread use of sensors on smartphones, it is becoming easier to use pedestrian dead reckoning (PDR) with smartphones, and making it possible to rely on smartphones for accurate indoor positioning. The existing PDR model is based on two-dimensional effective modelling method of the indoor space, said lack of three-dimensional space. In this paper, the concept of step height is introduced in a creative way, and a three-dimensional PDR model based on gait recognition is proposed, which makes it possible to locate indoor three-dimensional space. The three-dimensional PDR model uses an improved method of step detection and the average accuracy of the model is higher than the traditional 2D PDR model. Meanwhile, the experiment also proved the effectiveness and practicality of the three-dimensional model of the PDR.
Keywords: three-dimensional pedestrian dead reckoning; 3D-PDR; step detection; gait recognition; step height estimation; modelling.
Travel pattern modelling and future travel behaviour prediction based on GMM and GPR
by Wen Shen, Zhihua Wei, Chao Yang, Renxian Zhang
Abstract: How to use historical data of public smart card to predict user behaviour attracts a lot of attention. This paper aims at modelling travel patterns and predicting future travel behaviour of metro system smart card holders. We apply Gaussian mixture model (GMM) on time series to model user behaviour. We propose a new method based on the perplexity for finite GMM and use expectation-maximisation (EM) algorithm to estimate parameters of GMM. In order to predict the future travel behaviour, we introduce the Gaussian process regression (GPR) to define distributions over GMM, which can not only tell the probability of travelling at a certain moment but also tell the reliability of the prediction. Experimental results show that our whole system in the centre of GMM and GPR can effectively mine the hidden knowledge of historical data of smart card, and thus model the travel patterns and predict future travel behaviour.
Keywords: Gaussian mixture model; GMM; perplexity; Gaussian process regression; GPR; travel pattern modelling; behaviour prediction.
DEVSServer: ambient intelligence and DEVS modelling-based simulation server for epidemic modelling
by Mostefa Mokaddem, Baghdad Atmani, Abdelmalek Boularas, Chihab Eddine Mokaddem
Abstract: To improve disease surveillance systems (DSS) with faster and accurate outbreak detection and epidemics propagation capabilities, the availability of fine-tuned models is required along with the design of server-based solutions that simulate the effects of public health authorities' measures and integrate ambient intelligence (AmI) capabilities to semantise epidemic models. Hosting discrete event system specifications (DEVS) models, these AmI servers and their communication protocols are different, miscellaneous and require interoperability. The triple-space computing (TSC) paradigm addresses interoperability by sharing information represented in a semantic format through a common virtual space. In this paper, we present DEVSServer, a fully distributed TSC simulation server solution (middleware) designed to meet the needs of parallel and distributed discrete event simulation. DEVSServer defines a service oriented architecture (SOA) interface for the TSC operations. This interface complies with DEVS formalism and focuses on simplicity, conviviality and modularity, so that a single or many simulations that support different models can still interact. To assess DEVSServer, we provide a tuberculosis epidemic model simulation in time-varying temporal network with genetic programming immunisation strategy approach.
Keywords: ambient intelligence; AmI; triple space-based computing; TSC; service oriented simulation; parallel discrete-event simulation; PDES; disease surveillance system; epidemic modelling; temporal network; genetic programming; immunisation strategy.
Finite-time synchronisation of memristive hyperchaotic circuit based on Lorenz system with transmission delay
by Hongjuan Wu, Xiang Hu, Yuming Feng
Abstract: In this paper, we analyse the characteristics of one type of circuit structure that is extended from simplified Lorenz system by taking a memristor as feedback. Considering the transmission time delay between master system and slave system, we used a compound finite-time synchronisation signal controller, which consists of a general feedback control signal and a fine adjustment signal, to ensure the synchronisation of two memristive hyperchaotic circuits based on Lorenz system. Based on Lyapunov stability theory, finite-time control, matrix inequality, and considering the transmission time delay, the finite-time synchronisation condition for this type of memristive hyperchaotic circuit based on Lorenz system with transmission time delay via finite-time controller is given. Finally, simulation results are used to verify the feasibility and effectiveness of this method.
Keywords: memristor; Lorenz system; transmission time delays; finite-time; synchronisation.
Special Issue on: I3M 2017 Systems Modelling and Real-World Industry 4.0 Applications
Investigating small and medium-sized manufacturing enterprises immediate response and short-term recovery from flooding using an agent-based approach
by Meshal Alharbi, Graham Coates
Abstract: The predominance and economic significance of Small and Medium-sized Enterprises (SMEs) means widespread disruption can have severe financial consequences for a nation. This paper presents an agent-based approach enabling simulations to investigate manufacturing SMEs immediate response to and short-term recovery from a flood event to evaluate the effectiveness of combinations of inundation precautions. Manufacturing SME agents exhibit pre- and post-flood behaviours gleaned from interviews with such businesses that have flood experience. Based on a flood event simulated for Sheffield in the UK, results show an individual SME with most precautions implemented in the lightly or moderately flooded area can return to 100% production approximately 7 days earlier than if the fewest precautions were employed. Further, considering the average short-term recovery of all SMEs with most precautions implemented in the lightly or moderately flooded area, 100% production can be achieved almost 20 days before manufacturers located in the severely flooded area.
Keywords: small and medium-sized enterprises; agent-based modelling and simulation; flooding; short-term recovery; manufacturing.
Sustainability of retail store processes: an analytic model for economic and environmental evaluation
by Eleonora Bottani, Giorgia Casella, Simona Arabia
Abstract: This study proposes a model to evaluate the economic and environmental sustainability of retail stores. The model was developed under Microsoft Excel and reproduces the main retail store processes (i.e. product receiving, backroom storage, sales area management and return management) in quantitative terms. As input, the model takes several data about these processes; as output, it provides an evaluation of the total cost and CO2 emissions of the store. The application of the model to a real case, referring to a large-scale retail store of Italy, and the discussion of the key results obtained is presented for all the processes considered. The outcomes show that the most relevant environmental impact and the highest total cost are generated by the sales area management process. Conversely, the return management process contributes to the total cost to a limited extent. A sensitivity analysis was carried out to highlight the key aspect managers should focus on to improve the sustainability of the retail store. The results obtained provide useful guidelines for store managers to optimize the sustainability of their internal processes.
Keywords: sustainability; large-scale retail store; case study; economic and environmental assessment; analytic model.
Properties modelling as design by contract for cyberphysical systems: an example in the smart grid domain
by Andrea Tundis, Max Muhlhauser
Abstract: The development of a cyberphysical system is strongly related to the elicitation of requirements and their fulfilment. Requirements represent the agreement, among the actors involved in the development process of a system (e.g. stakeholders, engineers), of what it is expected to be delivered. As they are neither computable nor verifiable, because typically expressed textually, their misunderstanding could lead to delay or even the failure of the overall system development. In this context, the exploitation of the Properties Modelling (PM) approach combined with the simulation is proposed to enable assessable requirements. In particular, PM is adopted for expressing requirements as computable and verifiable components, whereas simulation techniques are exploited for supporting their automatic verification and to evaluate their level of fulfilment. The simulation model along with the results gathered from the properties evaluation represent the contract (Design-by-Contract) on which the actors can agree before the realization of an actual cyberphysical system. The proposal is tested in the smart grid domain.
Keywords: systems engineering; cyberphysical systems; properties modelling; requirements specification; simulation-based verification; smart grids.
Collaborative training in a virtual environment to increase productivity in a shipyard
by Jose Antonio Muiña Dono, Adolfo Lamas Rodriguez, David Chas Alvarez
Abstract: The paper addresses the potential of the combined use of simulation tools and a game engine for an effective and efficient design to study complex problems. This study is focused on the shipbuilding problem, although the methodology and tools proposed can be extended to another application by other complex problems reaching the same satisfactory results. The innovative use of both tools has important advantages. From the training point of view, an economic saving, dynamism, customisation and motivation could be achieved, facilitating the implementation of a new work culture in the company. In addition, the realism of the simulation makes easier the extrapolation of knowledge to the reality and an estimation of the performance of the improvements. On the other hand, streamlining model development processes is possible using the users as a testers and developers of the model, since the opinions of the users back to the system design.
Keywords: simulation; discrete event simulation; game engine; training; shipbuilding.
An investigation of the interactions between psychosocial risk factors and their health impact: mechanisms and consequences
by Hossein Abaeian, Mohamed Al-Hussein, Osama Moselhi
Abstract: Despite the increase in research on psychosocial hazards, studies have been unable to evaluate the inter-relationships among Psychosocial Risk Factors (PRFs) from a risk network perspective, and their findings are usually limited to bi-variate relationships between PRFs and their adverse outcomes. Also, they are unable to draw the pathways by which PRFs can affect workers health leading to impaired job performance. The present study performs a comprehensive literature review on the psychosocial risk-related research and provides an evidence-based list for major PRFs. In addition, social network analysis is implemented for developing the psychosocial risk network for further evaluation of the interactions between variables, leading to the identification of key PRFs that play important roles in structuring the entire risk network. In the next step, a system dynamic model is developed to provide the mechanism underlying the development of musculoskeletal disorders and productivity loss due to exposure to psychosocial stressors.
Keywords: psychosocial risks; mental process model; strain; impaired job performance; musculoskeletal disorders; system dynamics simulation model; dynamic thinking; social network analysis.
Special Issue on: I3M 2017 Concepts and Methodologies for the Next Generation of Modelling and Simulation Techniques in Industry and Logistics
Individualised modelling of affective data for intelligent tutoring systems: lessons learned
by Keith Brawner
Abstract: One on one tutoring from human expert tutors to human students is the most effective form of instruction found to date. There are many actions that human tutors perform that make them remarkably effective, including the attention that they pay to the cognitive and affective states of the human students that they tutor; and the use of this knowledge to modify the way that they instruct the material. According to theoretical models, learner state data is used to inform instructional data and decisions, which then influences the learning of the student. Naturally, the data about student state must be available in order to be used to adjust the instruction. Success amongst operational systems, however, has been observed with generalised modelling techniques. Individualised and adaptive modelling techniques from other domains in the literature present an alternative to the approach which isnt observing significant operational success. This paper investigates individualised adaptive models, validates the approach, and shows that it can produce models of acceptable quality, but that doing so does not obviate the experimenter from creating quality generalised models prior to individualising.
Keywords: adaptive and predictive computer-based training; intelligent tutoring systems; architectural components; emerging standards.
Identifying and modelling correlation between airport weather conditions and additional time in airport Arrival Sequencing and Metering Area
by Margarita Bagamanova, Juan Jose Ramos Gonzalez, Miquel Angel Piera Eroles, Jose Manuel Cordero Garcia, Alvaro Rodriguez-Sanz
Abstract: Different uncertainties during operational activities of modern airports can significantly delay some processes and cause chain-effect performance drop on the overall Air Traffic Management (ATM) system. The decision-making process to mitigate the propagation of perturbations through the different airport processes can be improved with the support of a causal model, build with a use of data mining and machine learning techniques. This paper introduces a new approach for modelling causal relationships between various ATM performance indicators, which can be used to predict by the means of simulation techniques the evolution of airport operations scenarios. The analysis of reachable airport states is a relevant approach to design mitigation mechanisms on those perturbations which drive the system to poor KPIs.
Keywords: ASMA time; holding; inbound traffic; weather impact; Bayesian networks; Coloured Petri net; airport; decision support tool.
Surrogate-assisted microscopic traffic simulation-based optimisation of routing parameters
by Bernhard Werth, Erik Pitzer, Christian Backfrieder, Gerald Ostermayer, Michael Affenzeller
Abstract: Reactive and predictive routing algorithms have to work fast and reliably for a large number of traffic participants. Therefore, simple rules and thresholds guide routing decisions rather than extensive data collection and machine learning. We optimize some of the thresholds governing the behavior of the PCMA* routing algorithm, by use of the microscopic traffic simulator TraffSim. Microscopic traffic simulation is more exact than its macroscopic counterpart and very well suited to test the efficiency of a reactive/predictive routing algorithm. Sadly, it is also tremendously more computationally expensive, impairing the applicability of 'conventional' heuristic optimization techniques like genetic algorithms or evolutionary strategies. Extensive use of surrogate models in an optimisation procedure is a promising alternative. Several variations of the efficient global optimisation algorithm (EGO) are tested and compared. Furthermore, a new type of surrogate model geared towards overcoming some characteristics of the parameter optimisation is presented.
Keywords: surrogate assisted optimisation; microscopic traffic simulation; TraffSim; HeuristicLab; efficient global optimisation; noisy optimisation; routing algorithms.