International Journal of Simulation and Process Modelling (20 papers in press)
- Evaluating policies using agent-based simulations: investigating policies for continuity of care
by Gregory Ramsey
Abstract: Anticipating effects of proposed clinical policies is a difficult task. This study investigates the usefulness of agent-based simulations for evaluating clinical policies. Two policies for continuity of care for patients with type 2 diabetes are investigated using an agent-based simulation. Computational models of a dynamic decision environment were simulated to determine aggregated effects of individual care-providing agents acting to achieve clinical goals. The simulated policies were: (1) continuous care (CC), where each patient was randomly assigned a specific physician model for care across visits, and (2) opportunistic care (OC), where each patient on each visit was randomly assigned to a physician model for treatment. These policy scenarios are at the crux of a debate as to whether continuity of care needs to be administered by a single provider or by a single organisation (e.g., clinic). The study determines under which conditions CC and OC policies result in favorable patient outcomes.
Keywords: clinical policies, agent-based simulations, type 2 diabetes, continuity of care, policy simulations
- Using simulation in verification of a mathematical model for predicting the performance of manual assembly line occupied with flexible workforce
by Atiya Al-Zuheri, Lee Luong, Ke Xing
Abstract: Designing a dynamic system with inherent randomness requires a predictable and dependable mathematical model accurately representing the essential aspects of real systems. So it is necessary to establish a confidence level in the mathematical model of this system by carrying out a verification process for this model to collect evidence. This paper deals with verification of the mathematical model designed for the predication of performance of manual assembly-lines occupied by a flexible workforce referred to as walking worker(s) assembly line (WWAL). To verify the mathematical model, the model was applied to an illustrative industrial example. Also experiments carried out on this example were simulated using a software package. Then, the predicted results of the mathematical model were compared with simulation results. Comparison leads to the verification of both the accuracy and the serviceability of the mathematical model developed.
Keywords: manual assembly line, WWAL, mathematical model, simulation, verification, randomness
- Modelling methodology for the simulation of manufacturing systems
by Reda Tajini, Saâd Lissane Elhaq, Ahmed Rachid
Abstract: Facing an increasingly competitive environment, companies must continually improve the performance of their production systems to respond to consumer demand that is increasingly unpredictable, unstable, and with competitive prices. This article is intended as a contribution to finding a solution to an emerging problem in the management of manufacturing flows in recent years, where product diversity, shortened lead times, and strong competition make the aspect of the 'flow' of goods from supplier to end customer a central one. In this perspective, the aim of this paper is to develop a flexible modelling environment for the simulation and analysis of production systems. This environment enables the decomposition of the production system, by offering generic and modular concepts for modelling the physical processes as well as the control processes to simulate the manufacturing processes as a whole. These concepts are specified and modelled using an object-oriented approach, such as the UML.
Keywords: manufacturing systems, manufacturing modelling, model reusability, model replication, simulation, optimisation, control systems, decision making, performance evaluation, UML, industrial case study.
- An object-oriented approach to port activity simulation
by Mikhail Kondratyev
Abstract: This paper discusses a technique for modelling cargo port activity. It is designed for a comprehensive evaluation of port efficiency under a given input of cargo traffic. An object-oriented extension of the conventional block-based approach to process-oriented discrete-event simulation is proposed to specify a model structure. A port modelling framework is implemented using the proposed technique and AnyLogic 6 simulation software. The framework consists of the custom AnyLogic library backed by a Java-based package of classes and interfaces. The library contains blocks, representing a set of typical vehicle handling processes in a port. The framework provides tools that allow for the rapid development of a cargo port model. It not only provides non-modifiable standard solutions but also allows thorough detailing of certain elements of the port infrastructure, if necessary.
Keywords: seaport infrastructure, port logistics, cargo traffic, discrete-event simulation, object oriented
modelling framework, AnyLogic
Special Issue on: "
I3M 2013 "Cutting-edge Methodologies, Applications and Technologies in Modelling and Simulation,"
- Military serious game federation development and execution process based on interoperation between game application and constructive simulators
by Changbeom Choi, Moon-Gi Seok, Seon Han Choi, Tag Gon Kim, Soohan Kim
Abstract: This paper proposes a development and execution process for military serious game federation, the Military Serious Game Federation Development and Execution Process (MSGFDEP). The MSGFDEP uses interoperation between an existing game application and constructive simulators to extend the serious game. In order to achieve the interoperation between the game application and constructive simulators, we use a High-Level Architecture (HLA). By interoperating a constructive simulator with an existing game application, a serious game developer can save effort by extending a serious game application, rather than building a serious game from scratch. The proposed methodology comprises two specified processes: federation development and federation execution. When the developer wants to build a serious game from scratch, the proposed methodology supports three specified processes: game loop analysis, game agent design, and development. On the other hand, when the developer wants to organise the federation with existing HLA-compliant serious game and constructive simulators, the methodology provides federation synthesis. Finally, the methodology defines the federation execution process to help trainees to obtain more experiences that are realistic.
Keywords: interoperation; system of systems; constructive simulator; serious game; virtual military training;
- Using the RetSim simulator for fraud detection research
by Edgar Alonso Lopez-Rojas, Dan Gorton, Stefan Axelsson
Abstract: Managing fraud is important for business, retail and financial alike. One method to manage fraud is by detection, where transactions etc. are monitored and suspicious behaviour is flagged for further investigation. There is currently a lack of public research in this area. The main reason is the sensitive nature of the data. Publishing real financial transaction data would seriously compromise the privacy of customers and companies alike. We propose to address this problem by building RetSim, a multi-agentrnbased simulator (MABS) calibrated with real transaction data from one of the largest shoe retailers in Scandinavia. RetSim allows us to generate synthetic transactional data that can be publicly shared and studied without leaking business-sensitive information, and still preserve the important characteristics of the data. We then use RetSim to model two common retail fraud scenarios to ascertain exactly how effective the simplest form of statistical threshold detection could be. The preliminary results of our tested fraud detection method show that the threshold detection is effective enough at keeping fraud losses at a set level, and that there is little economic room for improved techniques.
Keywords: privacy; anonymisation; multi-agent-based simulation; MABS; ABS;
retail store; fraud detection; synthetic data
- An intuitive and efficient approach to integrated modelling and control of three-dimensional vibration in long shafts
by Geoff Rideout, Ahmad Ghasemloonia, Farid Arvani, Stephen Butt
Abstract: Long, slender rotating shafts are susceptible to potentially destructive vibration, the severity of which depends on boundary conditions, geometry, and excitation. Examples of such shafts are truck driveshafts and mine or oilwell drillstrings. A nonlinear three-dimensional bond graph-based shaft model is presented, in which axial, torsional, and lateral vibrations can be predicted. Rigid lumped segments with six degrees of freedom are connected by axial, torsional, shear, and bending springs to approximate continuous system response. Parasitic springs and dampers are used to enforce boundary conditions. Additionally, the shaft can come into contact with surrounding objects. Normal contact forces are generated with a stiff spring, and sliding friction forces during contact are incorporated using coordinate transformations and dynamic Coulomb friction. The model is easily reconfigurable for different boundary conditions, and the bond graph formalism facilitates the inclusion of (semi-)active control submodels such as electromechanical actuators or dampers. The model is applied to an unbalanced rotating 80-metre oilwell drillstring collar section. Thirty segments are sufficient to predict the lowest natural frequencies and static deflection accurately. Simulations show realistic axial, torsional and lateral vibration, with lateral vibration comparable to a finite element model against which preliminary validation is done. Active lateral vibration control is implemented, in which actuators and strain gauges are placed 90-degrees apart around the pipe walls at multiple locations. A proportional controller acting on the strain gauge output significantly attenuates vibration and reduces wellbore contact.
Keywords: multibody dynamics; bond graph; lumped segment; drillstring; shaft vibration
Special Issue on: "
I3M 2013 "Modelling and Applied Simulation Multi-Perspective and Multidisciplinary Approaches,"
- An integrated approach for demand forecasting and inventory management optimisation of spare parts
by Mattia Armenzoni, Gino Ferretti, Roberto Montanari, Eleonora Bottani, Giuseppe Vignali, Federico Solari, Marta Rinaldi
Abstract: In this paper, we develop and test an advanced model, based on discrete-event simulation, whose purpose is to forecast the demand for spare parts during the whole lifetime of a complex product, such as an industrial machine. To run the model, the relevant data of the product (i.e., the industrial machine) manufactured by a targeted company should be collected. With those data, the model provides an estimate of the spare parts the company will have to supply during the machine lifetime, and therefore of the optimal level of spare parts inventory the company should keep available. The data provided by the model are subsequently applied to a case example, referring to a hypothetical company, manufacturing industrial plants. The application is carried out considering two scenarios, i.e. a traditional and an advanced approach for demand forecasting, this latter reflecting the circumstance where the company makes use of the proposed forecasting method to estimate the spare parts demand. The comparison of the outcomes obtained in the two scenarios highlights the efficiency and resolution capacity of the model developed. Moreover, from the application, some important considerations are drawn as regards the potential savings that can be achieved by means of an advanced demand forecasting method, such as that enabled by the model developed in this paper.
Keywords: spare parts, simulation, demand forecasting, stock management.
- An agent-based electronic market simulator enhanced with ontology matching services and emergent social networks
by Virgínia Nascimento, Maria João Viamonte, Alda Canito, Nuno Silva
Abstract: AEMOS is a simulator that aims to support the development of agent-based electronic markets capable of dealing with the natural semantic heterogeneity present in this kind of environment. AEMOS simulates a marketplace that provides ontology matching services, enhanced with the exploitation of emergent social networks, enabling an efficient and transparent communication between agents, even when they use different ontologies. The system recommends possible alignments between the agents ontologies, and lets them negotiate and decide which alignment should be used to translate the exchanged messages. In this paper, we propose a new ontology alignment negotiation process, which promotes the reuse and combination of already existing alignments, as well as the involvement of business agents in the alignment composition process. With this new model, we aim to achieve a higher adequacy of the used alignments, as well as a more accurate and trustful evaluation of the alignments.
Keywords: agent mediated e-commerce, agent-based simulation, semantic interoperability, ontology alignment negotiation, ontology alignment evaluation, emergent social networks, social network based recommendations
- Multi-domain modelling and simulation of an automated manual transmission system based on Modelica
by Hua Huang, Sebastian Nowoisky, Rene Knoblich, Clemens Guhmann
Abstract: With the continuous growth in demand for lower emissions and higher riding comfort, the shift quality takes a more and more important role in automated transmission control algorithms. In order to effectively optimise the corresponding control parameters and functions in the transmission control units (TCU), the model-based calibration is a suitable method. For this purpose, a detailed dynamic model, which provides a virtual platform for the shift quality optimisation, is imperative and necessary. In this paper a 5-speed automated manual transmission (AMT) is used as a research object, and a detailed Modelica
Keywords: automated transmission, hydraulic, multi-domain modelling, model-based calibration
- An ontologic agent-based model of recreational polydrug use: SimUse
by Francois Lamy, Terry Bossomaier, Pascal Perez
Abstract: SimUse is an ontology-based social simulation model aiming at reproducing trajectories of recreational poly-drug users. To describe and capture the complexity of this phenomenon, we bring together empirical evidence from ethnography with theoretical constructs from sociology and neuroscience into an agent-based model. After reviewing the context of recreational poly-substance use and justifying our approach, this paper describes the multi-layered structure of the simulation and details some of the key aspects of SimUse. We illustrate the capacity of SimUse to reproduce neurophysiological reactions to substance use and to explore what-if? scenarios related to drug use.
Keywords: polydrug use; agent-based model; social simulation; sociology of deviance
- Dynamic optimal power flow control with simulation-based evolutionary policy-function approximation
by Stephan Hutterer, Michael Affenzeller
Abstract: In current operations research, dynamic optimisation problems are a central and challenging research topic. Especially in complex real-world systems, such as electric power grids, dynamic problems occur where robust solutions need to be found that enable (near-)optimal control over time in volatile as well as uncertain power grid operation. This paper identifies the application of policy-function approximation for such problems. Here, an analytic function is aimed to be found, which takes a state of the dynamic system as input and directly derives control actions that lead to approximate optimal operation at runtime, without the need for embedded optimisation. Applying this approach to two popular and scientifically challenging problem classes in power grids research, this work aims at providing a general view on this optimisation concept. Therefore, a dynamic generation unit control task will be experimentally treated on the one hand, while dynamic load control under uncertainty with electric vehicles represents the second use case. Both applications are related to dynamic stochastic optimal power flow problems, hence, show the successful application of policy-function approximation to this problem domain.
Keywords: simulation optimisation, power flow control, dynamic stochastic optimisation problems, policy-function approximation
Special Issue on: "
I3M 2013 Cutting-edge Methodologies, Applications and Technologies in Modelling and Simulation,"
- Production function implementation in an agent-based simulation
by Roman Šperka, Marek Spišák
Abstract: The aim of the paper is to describe the seller-to-customer negotiation in the business processes (sales) of a virtual company. Based on it, we propose an innovative approach to simulate, investigate and predict some of the key performance indicators of a trading company. The methods used to implement the simulation framework in the form of a multi-agent system come out of the agent-based modelling and simulation techniques. The paper firstly presents some of the existing theories about consumer behaviour and the types of factor influencing it. Secondly,the paper characterises a multi-agent model of a virtual company, the agents participating in the seller-to-customer negotiation, and the production function. Finally, the simulation results and their validation are described. To conclude, the proposed approach with the use of seller-to-customer negotiation could properly contribute to better decision-making process of a company's management.
Keywords: system; simulation; virtual company; multi-agent system; negotiation; decision support
Special Issue on: "AMEE 2013 Advances in System Simulation"
- A comparison of machine learning techniques for medical data classification
by Lei Shi
Abstract: Research in medicine and molecular biology has accumulated enormous amounts of medical data. Such large amounts of data must be thoroughly analysed to gain useful information. Recently, many researchers have been attracted to study this problem. As an effective tool, machine learning methods are the best candidates for this challenging task. This paper aims to assess several machine learning techniques, including support vector machines, artificial neural networks, decision tree and random forest, and then to compare the performance of these methods for automated classification of medical data.
Keywords: support vector machines, artificial neural networks, decision tree, random forest
Special Issue on: "Simulation and Process Modelling in Safety and Emergencies"
- Dynamics of software systems projects during the requirements process improvement
by Aminah Zawedde, Ddembe Williams
Abstract: Requirements Process Improvement (RPI) in software systems projects has received much attention from both researchers and practitioners. RPI is aimed at systematically controlling changes in the requirements process, and making improvements that result in good quality requirements specifications at reduced costs and delivered within the specified schedule. RPI activities are dynamic and complex processes managing all changes to the requirements process. Therefore, in order to meet customer, business and regular industrial needs, organizations need to have an effective RPI that will result in quality requirements, and work within the stipulated budget and schedule. This paper explores the dynamics that exists among the factors that influence a successful RPI in order to provide the understanding required to explain how the underpinning process attributes affect the quality and associated costs of the RE specification delivered to the customer. A systematic approach for RPI has been used to provide the understanding required by process improvement teams in order to effectively undertake process improvement. The authors contend that the developed system dynamics-based quality-cost RPI model is a generic framework for an effective approach to RPI. The model allows a systematic inquiry that yields explanations and provides RPI stakeholders with a common decision-making framework. The model was validated by practising process improvement consultants and managers, and makes a contribution towards understanding the quality-cost dynamics of requirements process improvement.
Keywords: software systems; cost; quality; schedule; RPI; system dynamics modelling
- Sample average approximation method for the chance-constrained stochastic programming in the transportation model of emergency management
by Deng Chunlin, Yang Liu
Abstract: This study proposes a stochastic programming model for the transportation of emergency resources during the emergency response. Since it is difficult to predict the timing and magnitude of any disaster and its impact on the urban system, resource mobilisation is treated in a random manner, and the resource requirements are represented as random variables. Randomness is represented by the chance constraints in this paper. To deal with the difficulty in calculating the chance constraint function, we use Conditional Value at Risk (CVaR) to approximate the chance constraint, and solve the approximation problem of the chance-constrained stochastic programming by using the sample average approximation (SAA) method. For a given sample, the SAA problem is a deterministic non-linear programming (NLP) and any appropriate NLP code can be applied to solve the problem. The model and method provide a new way for the emergency logistics management engineering.
Keywords: emergency management engineering; chance constraint; conditional value-at-risk; sample average approximation; transportation model.
- Quantitative method on miners emergency response capacity
by Jiangshi Zhang, Pan-pan He, Shu-shan Gao, Jia Tao
Abstract: In order to realise optimal selection of key posts and reduce human-initiated accidents in coal mines, a fuzzy comprehensive evaluation model is established for miners emergency response capacity, together with an index system. Firstly, a hierarchical structure that has four first-level indexes and 14 second-level indexes is constructed taking account of literature dependence and safety engineering practices. Secondly, all indexes weights are determined by means of the Analytic Hierarchy Process (AHP), which is widely used to identify indexes relative importance. Thirdly, the fuzzy comprehensive evaluation method based on fuzzy mathematics is used to study each indexs weight distribution, and a total score is calculated in fuzzy evaluation. Finally, we take some coalmines as examples to illustrate the validity of the proposed evaluation model, and countermeasures can be put forward to improve miners emergency capability in accordance with evaluation results.
Keywords: miners; emergency capability; quantitative method; analytic hierarchy process; AHP; fuzzy comprehensive evaluation
- Electric vehicle industry development environment evaluation in China based on BP neural network
by Chuansheng Xie, Chenchen Zhao, Dapeng Dong, Pengyuan Zhong
Abstract: As an emerging industry of energy conservation and environment protection, the electric vehicle industry has broad prospects for development. However, it is currently in the initial stage and the development environment is complex, so it is very necessary to study the development environment. This paper combines an electric vehicle industry development environment evaluation index system with the BP neural network to establish an electric vehicle industry evaluation model. Then the indicator score values as training samples obtained from the use of expert scoring method are imported to the BP neural network evaluation model. After training and testing the neural network, this paper compares the testing results with the results based on AHP and fuzzy comprehensive evaluation method, to test the validity of the evaluation model. The result shows that evaluation model based on BP neural network can effectively improve the reliability and accuracy of evaluation results.
Keywords: electric vehicle industry; BP neural network; environment evaluation
Special Issue on: "Simulation and Process Modelling in Safety and Emergencies,"
- Research on probability of default prediction based on loan companys credit fund trading behaviours
by Bo Hong, XingSheng Xie, HaoMing Guo
Abstract: The probability of default (PD) is an important parameter to quantify credit risk, which is the foundation in construction of the internal rating-based (IRB) systems of commercial banks, and is usually impacted by some less frequent accidents, such as market factors or the macroeconomic climate changes. The traditional approaches to estimate PD, such as expert method or statistical pattern classification, are heavily dependent on annual financial reports, which are usually provided by the borrow-customer themselves, and can lead to unreliability and long time lags in forecast. In the light of the business schema of credit fund expenditure surveillance in some commercial banks in China, this paper proposes a Support Vector Machine (SVM) classifier model to predict PD based on a set of loan fund expenditure behaviour features. Quite different from the traditional PD classifier models, which are based on financial indicators of factors, our SVM classifier is constructed based on a set of loan fund expenditure behaviour features, which can be directly collected from the fund trading databases of commercial banks in time. For the sake of modelling effect comparison, both the Logistic model and the SVM are used in this paper to classify and predict PD. The Logistic regression classification accuracy is near 84.6%, whereas the SVM classification accuracy rate can be up to 89.4%.
Keywords: climate changes; probability of default; credit risk; classifying and predicting; credit fund trading behaviours
- Managerial equity incentive, corporate risk-taking and corporate performance
by Jianghong Zeng, Linping Tan, Xiaohong Chen
Abstract: Based on data from the equity incentive plans of Chinese firms listed on the stock market between 2006 and 2011, this study empirically investigates the relationship between managerial equity incentive, corporate risk-taking and corporate performance. The paper first uses the volatility of corporate earnings in order to measure the degree of corporate risk-taking, and the findings suggest that there is a significantly positive association between managerial equity incentive and corporate risk-taking. Moreover, compared with lower level staff, the risk-taking effect on managers is stronger. Additionally, the degree of corporate risk-taking of the sample in China is low. Therefore, an increase in the level of corporate risk-taking can considerably increase the firms value. This paper also uses the volatility of stock returns as a proxy variable of the degree of corporate risk-taking, and the findings do not change substantially.
Keywords: executive stock options; risk-taking incentives; firm value