International Journal of Simulation and Process Modelling (42 papers in press)
Solving preemptive job-shop scheduling problems using a true concurrency model
by Farid Arfi, Jean-Michel Ilié, Djamel-Eddine Saidouni
Abstract: A true concurrency model called Stopwatch Durational Action Timed Automata (S-DATA) is proposed to model preemptive timed concurrent systems. We demonstrate its usefulness in tackling the preemptive job-shop scheduling problem (PJSSP). This yields a compact reachability tree representing the possible schedules such that the durations and preemptions of the scheduled actions are dynamically managed. Different techniques are demonstrated to reduce the space search over such reachability tree, preserving the optimal schedules of the problem. The efficiency of approach is tested on a number of well-known benchmark problems and compared with the best method of scheduling in common use.
Keywords: job-shop; preemption; modelling; true concurrency; reachability; scheduling.
Mathematical modelling of vehicle assembly line for throughput enhancement
by Arun Rane, Vivek Sunnapwar
Abstract: Continuous improvement in manufacturing to give a cutting edge over the competitors is todays compulsion. The vehicle assembly line, being one of the most complex assembly lines, has been an area of active research over past few years and has attracted many researchers. The objective of this work is to improve the performance of vehicle assembly lines by developing suitable mathematical relations between various parameters that influence throughput. This work also systematically identifies and unfolds different approaches adopted by various research scholars through systematic review of peer-reviewed papers from reputable journals.
There are several uncertainties in the manufacturing environment. Here, mathematical models are developed to consider the impact on throughput of important influencing factors such as equipment failure, shortage of materials, absenteeism, set up, material handling, rejection and fatigue. Then, inter-relationships are established between these parameters. Further, an attempt is made to develop relationships between these parameters and their corresponding costs. Relationships are established scientifically using regression modelling, Matlab, Minitab, Excel, Arena and discussions with domain experts. These are validated with real world data.
Practitioners may use these models to predict and control uncertainty. Further, within a given cost constraint and using lean techniques, cycle times may be reduced in order to increase the output. This has been demonstrated in a real world case study done for a period of one year in a reputable vehicle assembly manufacturing plant.
Keywords: simulation, optimisation, lean, mathematical modelling, line balancing, throughput, efficiency.
Simulation-based fleet scheduling in the Metrobus
by Engin Pekel, Selin Soner Kara
Abstract: A successful fleet scheduling is important in any public transport system. Metrobus is a bus rapid transit (BRT) system in Istanbul and has a high usage percentage among the public transport. The aim of this study is to establish a successful fleet scheduling by using simulation in the Metrobus. In addition, it aims to meet the satisfaction of passengers. Metrobus system is regarded as a discrete system in the study. The distributions of the passengers who are boarding and disembarking the system are determined with regard to a stochastic process, and a discrete-event model is constructed to determine at which bus-stop one boards and disembarks from the Metrobus. A simulation experiment is presented with the results by applying several different scenarios. At least 12.7% decrease in queueing for Zincirlikuyu direction and at least 9.9% decrease in queueing for Avcılar direction are achieved in the developed simulation model. The results prove that simulation-based fleet scheduling can be successfully applied for a Metrobus.
Keywords: bus rapid transit; fleet scheduling; input analysis; public transport; simulation
Modelling and simulation of an inclined fuel transfer machine in a prototype fast breeder reactor operator training simulator
by Bindu Sankar, T Jayanthi, Jaideep Chakraborty, H Seetha, A Venkatesan, K Madhusoodhanan, S.A.V. Satya Murty
Abstract: The Indira Gandhi Centre for Atomic Research at Kalpakkam has successfully designed a 500 MWe Prototype Fast Breeder Reactor (PFBR). It is a proven fact that the critical factor in ensuring safe and reliable operation of any nuclear power plant is a qualified and well-trained personnel, and hence the need for operator training using a simulator. Fuel handling is one of the most important subsystems in a PFBR. Ex-vessel subassembly transfer is done using an Inclined Fuel Transfer Machine (IFTM), which operates remotely and safely. Using the IFTM, fresh fuel assemblies are loaded into the reactor, and spent fuel assemblies get unloaded. This paper deals with modelling and simulation of the operations of IFTM in the simulator. Virtual panel models and control logic models were modelled using modelling tools present in the simulator. The process modelling was developed in-house using platform-independent C++ code with 3D models.
Keywords: animation, fuel handling system, prototype fast breeder reactor, simulator, inclined fuel transfer machine, operator training, nuclear power plant, full scope replica simulator, operator training simulator, ex-vessel fuel handling, transfer arm, virtual panel, handling control room, Kalpakkam breeder simulator, cell transfer machine
A mining approach for component abnormal information based on monitor log
by Jinfu Chen, Lili Zhu, Yuchi Guo, Rubing Huang
Abstract: A software component is an assembly unit that can be deployed independently in any software system. Because the source code and development documents of a software component cannot be obtained, the vulnerability testing for software components is a challenge for component users. Explicit and implicit vulnerabilities are two common security vulnerabilities in components. In this paper, in order to detect security vulnerabilities in the component under test effectively, a mining approach for component abnormal information based on monitor log is proposed. For explicit vulnerability, the monitor log is mined with the improved Apriori algorithm, and the risk coefficient of each method in components is calculated with the frequent item sets algorithm based on the mining results. For implicit vulnerability, all the method execution sequences in the monitor log should be extracted and stored into database to establish a method sequence database. The vulnerability testing report is obtained by mining the method sequence database with the improved GSP (Generalized Sequential Patterns) algorithm after data preprocessing. An empirical study based on the proposed method is conducted, and the experimental results show that the approach to mine component abnormal information can effectively detect security exceptions of the component under test.
Keywords: component testing; explicit vulnerability; implicit vulnerability; Apriori algorithm; GSP algorithm.
Modelling and optimisation of train electric drive system based on fuzzy predictive control in urban rail transit
by Yeran Huang, Fang Cao, Bwo-Ren Ke, Tao Tang
Abstract: Electric vehicles are widely applied in urban rail transit systems. By executing control commands of the signaling system, the AC electric driver system converts electrical energy into mechanical energy to drive trains in traction mode. On the contrary, the mechanical energy is converted into electrical energy of contact line in braking mode. In this paper, the train traction system is modelled in MATLAB/Simulink to simulate the train operation process. Transmission loss and resistance force changes are considered particularly. In most trains, the PI control method is used in induction motor driver control for speed control. Compared with DC motor driver, the induction motor is difficult to control as the workhorse of the electric driver system because of variable parameters and complex dynamics. The fuzzy predictive control method is proposed in this paper to improve the tracking precision of the control system and to keep a steady state of contact line voltage with the formulated train traction model. Based on the Beijing Yizhuang line, the effectiveness of the model and the good performance of fuzzy predictive control are validated and compared with the traditional PI control method.
Keywords: modelling; electric drive system; fuzzy predictive control; urban rail transit
Semantics of multisampling systems
by Fernando Barros
Abstract: We present the semantics of the Continuous Flow System Specification (CFSS). CFSS is a modular formalism able to describe hierarchical sampling-based systems with a time-varying topology. CFSS introduces the concept of multisampling to achieve a description of continuous signals on digital computers. Sampling is treated as a first order concept being explicitly supported. Traditional discrete time machines operate at the same rate simplifying the semantics of their interconnection. However, complex systems require machines to specify their sampling rate independently, making their coordination a challenging problem. The CFSS formalism enables sampling to change over time and from component to component, making CFSS a framework for representing multisampling systems. The ability to join machines with different sampling periods is enabled by a novel representation of continuous systems based on digital computers. We illustrate multisampling in the context of a temperature control system that uses independent sampling rates to represent a digital controller and a numerical solver. We also illustrate the ability of CFSS to represent models with a dynamic topology.
Keywords: continuous systems; sampled-based systems; modeling & simulation semantics
Simulation of complex regional technology innovation ecosystem under resource constraints
by Tie Wei, Zhiwei Zhu, Lei Lei, Ron Cheek
Abstract: The development of a Regional Technological Innovation Ecosystem (RTIE) under resource constraints is uncertain and complex. Based on the complex systems theory, this paper discusses the evolution of RTIE through modelling and the simulation of a Multi-Agent System(MAS). Specifically, it proposes a theoretical model of RTIE under innovation resource constraints and explains the adaptive changes of the RTIE. It operationalises the concepts into dimensions of the quantified variables. Also, it uses the Swarm software to simulate the evolution of the RTIE under innovation resource constraints. The simulation model incorporates an environment of innovation resource constraints and various situations under the control policies. The results show that resource agents will gradually gather around Enterprise Agents. Enterprise and resource agents will be distributed differently in the regional space. The different control agents' actions may also lead to different evolution results. The study provides some theoretical foundations for future research in RTIEs evolution and regulation.
Keywords: resource constraints; regional technological innovation ecosystem; evolution; regulation; simulation
Negotiation model for knowledge management system using computational collective intelligence and ontology-based reasoning: case study of SONATRACH AVAL
by Noria Taghezout, Nawel Sad Houari, Nador Aissa
Abstract: This paper presents an agent-based approach that facilitates knowledge management and decision-making in maintenance field by enabling the collaboration and negotiation between experts in SONATRACH AVAL. The main objective of the suggested model is to treat the business rules with semantic errors that expert agents are asked to negotiate in order to accept or refuse a modification of rules. To do so, the expert manager can be represented by an intelligent agent that negotiates with experts (participants). We propose an interactive negotiation model using an extended version of the Contract Net Protocol (CNP) and an ontology named OntoloG. The experimental results show that the developed computation collective intelligence approach is very interesting and efficient for expert collaboration in the well-known petroleum enterprise in Algeria (SONATRACH).
Keywords: agents; knowledge management system; negotiation model; OntoloG ontology; expert agents; SONATRACH; contract net protocol.
Modelling and application for eclampsia with SimMom
by Xue Wang, Ying Pan, Liyou Song, Xiaochen Huang, Ming Liu, Anqi Liu
Abstract: In this paper, the issue of simulation-based education with SimMom is dealt with for training of the students and young doctors in obstetrics and gynaecology in the case of eclampsia in hypertensive disorders during pregnancy, together with the reasonable and standard drug treatment. The model is built and the practical training results are analysed and compared for the performance of two groups of students under model-based training and conventional training, respectively. The results show that there was no significant difference in the theoretical knowledge test and crossover test for the two groups of students, whereas practice test scores increased significantly (P<0.05), with the group using the model of SimMom scoring higher than the other group. It proves that the SimMom application in obstetrics eclampsia will help to improve medical students' and young doctors' clinical skills. The advanced product makes a great contribution to reducing the medical accidents, improving medicinal level and doctor-patient relationship and promoting medical education.
Keywords: SimMom, eclampsia, simulation-based education, medical modeling, clinical skill
Cost models for improved vehicle assembly line performance
by Arun Rane
Abstract: Viability of any manufacturing plant is function of time and cost. Automobile manufacturing is the most competitive sector. Objective of this paper is to provide detailed description of development of relationship between Cost of failure and time lost due to equipment failure, Cost of inventory and time lost due to shortages of material, Cost of setup and time lost due to set up, Cost of absenteeism and time lost due to absenteeism, Cost of material handling and time lost due to material handling. Relationships are established scientifically using Regression modeling, Simulation and discussions with domain experts. Results are validated in reputed vehicle assembly line. In this contribution it has been demonstrated that established models follows cubic relationship as against hyperbolic reported in literature. Further an improved model with strong 17 constraints is presented which may be useful for managers in taking cost based decisions to improve the throughput.
Keywords: Cost of inventory; Cost of failure; Cost of setup; Throughput; Vehicle assembly line.
Special Issue on: I3M 2014 Modelling and Applied Simulation for the 3rd Millennium Enhancements in Traditional Approaches and Moving towards Simulation as Service
A simulation optimisation-based approach for team building in cyber security
by Pasquale Legato, Rina Mary Mazza
Abstract: In this study we present a simulation optimisation (SO) approach based on direct search methods applied to cyber security. The problem consists in investigating if and when human resources (i.e. analysts) in a company should i) work alone or ii) work in consultation with teammates when responding to different attack rates and types targeting a predefined set of company cyber assets. The objective of the study is to evaluate overall attack tolerance with respect to system performance degradation and both resource training and knowledge gain. Numerical examples and experiments related to resource assignment and team formation are presented to show how the SO model can support company managers when grappling with a very common decision: make or buy cyber security knowhow.
Keywords: simulation optimisation, cyber security, team formation and collaboration
SLMToolBox: enterprise service process modelling and simulation by coupling DEVS and services workflow
by Gregory Zacharewicz, Hassan Bazoun, Judicael Ribault, Yves Ducq, Hadrien Boyer
Abstract: Market competition is pushing companies to differentiate themselves from competitors by developing customised services in addition to their original production (either physical or digital). It drives the emergence of service process modelling to describe more precisely the composition of services. Nevertheless, business initiatives modelling can be very complex to set, lying at the heart of many business decisions and demanding a lot of time and effort to handle and operate unambiguously. A well-designed and well-built business model can lower the risk of operating a service process, in consequence making enterprises more successful in their objectives. To this end, this paper recalls the MDSEA methodology and presents the key concept of the transformation of EA* and BPMN concepts into simulation workflows. Then it introduces the implementation done with the SLMToolBox that is an Eclipse RCP service graphical modeller, model transformer, and simulation engine. In more detail, it runs transformation from service processes models designed by business users to BPMN models. Then the BPMN models can be transformed to DEVS models to simulate the behaviour of the entire process model. In addition, enterprises are facing situations where future (undeveloped yet) enterprise services need to be integrated with existing ones. To go further and for a better integration and deployment of service models in the enterprise, we propose to combine service process M&S with service calls execution workflow. To achieve that goal, we are mashing up simulation of services modelled with existing enterprise web services calls. The interoperability between real and simulated services is handled by the tool Taverna Workflow and HLA RTI. This step is pushing one step further the expertise in the MDSEA methodology, attempting to pave the way from service design to IT development.
Keywords: modelling, simulation, workflow, BPMN, Taverna, service, model transformation
The packages clustering optimisation in the logistics of the last mile freight distribution
by Elvezia M. Cepolina
Abstract: The paper refers to the modelling and simulation of an innovative urban freight distribution scheme. Packages destined for receivers in an urban area are firstly delivered to the urban distribution centre (UDC); each package is characterised by an address and dimensions. The load units are consolidated in the UDC with packages. Each load unit is addressed to a temporary unloading bay, where receivers are thereafter in charge of collecting their packages. The paper concerns a methodology for the load units consolidation which minimises the overall distance travelled by receivers, taking into account the load unit capacity and the maximum walking distance for the receivers to accept and collect their packages. A fuzzy k-means clustering algorithm has been adopted. The fuzzy clustering algorithm is recalled by a simulation model of the proposed transport system. The methodology has been applied to the case study of historical city centre of Genoa, Italy.
Keywords: last mile freight distribution; load units consolidation; simulation; optimisation; fuzzy clustering algorithm.
Tactics for approaching cash optimisation in bank branches
by Miguel Aguilar Zaragoza, Idalia Flores de la Mota
Abstract: Maintaining a pre-defined level of service in many operations can be very expensive, especially if there are severe penalties when there is a lower level of service than the target. In such cases, companies seek to achieve goals even if that means significant losses in operating efficiency. In particular, banks, through their branches, offer cash transactions as a key service, so any lack of available cash is a critical issue, which would affect the prestige of the entire bank not just of that branch in particular. This paper aims to establish a policy, called a vault policy, that lets the cash administrator of a branch know how to manage the branchs money properly, by handling orders to the central vaults with realistic assumptions and easy-to-implement criteria. In order to achieve this, we present a model based on dynamic programming principles, to represent the problem and generate an input for the vault policy. Other inputs for the policy are some parameters set according to a branch's demand for a cash transactions approach, from the perspective of a best fit between frequentist and Bayesian, the latter with a recent development that more efficiently covers the Markov Chain Monte Carlo (MCMC) simulations. The demand of a cash transactions approach also helps to control the risk of stocking out and to project horizons of cash balances, given certain scenarios. With these inputs and a definition of some intuitive rules, we can implement and assess the vault policy. The results for 30 branches are presented.
Keywords: dynamic programming, compound process, generalised linear models, INLA, R, cash optimisation, bank branches.
Special Issue on: I3M 2014 New Advances in Simulation and Process Modelling Integrating New Technologies and Methodologies to Enlarge Simulation Capabilities
Cargo dynamic stability in the container loading problem: a physics simulation tool approach
by António Ramos, João Jacob, Jorge Justo, José Oliveira, Rui Rodrigues, António Gomes
Abstract: The container loading problem (CLP) is a real-world driven, combinatorial optimisation problem that addresses the maximisation of space usage in cargo transport units. The research conducted on this problem failed to fulfill the real needs of the transportation industry, owing to the inadequate representation of practical-relevant constraints. The dynamic stability of cargo is one of the most important practical constraints. It has been addressed in the literature in an over-simplified way, which does not actually translate into real-world stability. This paper proposes a physics simulation tool based on a physics engine, which can be used to translate real-world stability into the CLP. To validate the tool, a set of benchmark tests is proposed and the results obtained with the physics simulation tool are compared with the state-of-the-art simulation engineering software Abaqus Unified FEA. Analytical calculations have been also conducted, and it was also possible to conclude that the tool proposed is a valid alternative.
Keywords: dynamic stability, physics engine, container loading problem
Special Issue on: The Latest Technologies for Building a Smart City
A novel visible-infrared image fusion framework for smart cities
by Zhinqin Zhu, Guanqiu Qi, Yi Chai, Hongpeng Yin, Jian Sun
Abstract: Image fusion technology is widely used in different areas and can integrate complementary and relevant information of source images captured by multiple sensors into a unitary synthetic image. Image fusion technology, as an efficient way to integrate information from multiple images, plays a more and more important role in smart cities. The quality of the fused image affects the accuracy, efficiency, and robustness of the related applications. Existing sparse representation-based image fusion methods consist of overly complete and redundant dictionary learning and sparse coding. However, overly complete and redundant dictionary does not consider the discriminative ability of dictionaries that may seriously affect the image fusion. A good dictionary is the key to a successful image fusion technique. To construct a discriminative dictionary, a novel framework that integrates an image-patches clustering and online dictionary learning methods is proposed for visible-infrared image fusion. The comparison experiments with existing solutions are used to validate and demonstrate the effectiveness of the proposed solution for image fusion.
Keywords: image fusion; sparse representation; dictionary learning; sub-space clustering; smart city.
Container-as-a-service architecture for business workflow
by Ye Tao, Xiaodong Wang, Xiaowei Xu, Guozhu Liu
Abstract: The massive amount of data makes the work of building a smart city more and more data-driven. However, data collection and its analysis in such a large system are often separated and executed by different vendors. Owing to volume, security and privacy reasons, data migration can be difficult. To build a bridge between data owners and data analysers, service migration is applied, which forms the infrastructures, applications and services for different vendors. This paper presents a Container-as-a-Service (CaaS) framework for data processing in a smart city environment. We design and implement a multi-layered container service construction and deployment environment, and we employ the business workflow orchestration technologies in this environment. By using containers, local cluster resources are virtualised and isolated to simplify the creation and deployment of multiple applications autonomously across multiple vendor systems. Inside a container, computational tasks and worker processes are encapsulated into web services, in order to leverage service-based workflow technologies to develop timely and effective workflows for a smart city environment. A use case of smart transportation is studied to validate the usefulness and evaluate the performance of the presented architecture. Results show that the approach can be beneficial to the scientific tasks in regard to its flexibility and re-usability.
Keywords: container; service computing; scientific workflow; BPEL for web services; Hadoop.
Software behaviour analysis method based On behaviour template
by Yingxu Lai, Zenghui Liu, Tao Ye
Abstract: This paper proposes a software behaviour analysis method based on behaviour template (SABT) which, according to the context of source code, builds a behaviour template to detect software malicious behaviour based on a function transfer map and minimum function blocks. Many methods use state transfer diagrams to build software behaviour models. Our method is based on the corresponding relationship between the functions and system call sequence, which ensures accurate detection of malicious behaviour. Compared with traditional methods, such as N-gram, FSA, and Var-gram, SABT can get higher cover rate of code and detect abnormal behaviour more effectively and efficiently.
Keywords: software behaviour, software interrupt, behaviour template, minimum function block
Boundary estimating of urban road network for traffic impact analysis when reconstructing intersections: methodology and evaluation
by Yingying Ma, Ying Zeng
Abstract: Intersections are major points of conflict for road users and the key parts of urban road networks. It is necessary to reconstruct some intersections to improve capacity and safety. A methodology to estimate the boundary of a road network for traffic impact analysis of intersection improvements is discussed in this paper. Firstly, models are presented for two types of degree of correlation. The degree of saturation and free-flow travel time are considered in the model for the degree of correlation between two adjacent intersections, and the degree of correlation between any two intersections in the network is analysed using a Laplacian matrix algorithm. Secondly, a new method to estimating a road network boundary is proposed. Thirdly, two measures are adopted to evaluate the boundary of road networks: the minimum average cut degree of correlation and the minimum traffic influence on intersections outside the boundary. Finally, the method is demonstrated using a city road network. The results of the case study confirm the validity of the proposed approach.
Keywords: boundary estimating, traffic impact analysis, intersection reconstruction, Laplacian matrix
Knowledge extraction based on linked open data for clinical documentation
by Mazen Alobaidi, Khalid Mahmood, Susan Sabra
Abstract: Smart cities are becoming a reality in the near future to transform many sectors and activities in our lives. Smart city systems, such as healthcare systems, will have new functionality to improve the quality of life of its citizens. Electronic health records are an essential component of healthcare systems. They are valuable for medical research, but much of the information is recorded as unstructured free text. Knowledge extraction from unstructured text in electronic health records is a problem that is well-documented but still not totally resolved. Knowledge extraction is very challenging because medical language has ungrammatical and fragmented constructions. We have implemented a unique framework knowledge extraction based on linked open data for clinical documentation (KE-LODC) that generates accurate and high quality triples transforming unstructured text from clinical documentation into well-defined and ready-to-use linked open data for diagnosis and treatment. We used Name Entity Recognition and Disambiguation (NERD) because it proved to be highly more precise than other available tools in entity recognition. Our framework proved to produce highly qualified big number of triple candidates, which improves the likelihood of better classification. Also, we evaluate our framework by comparing its precision and recall with two benchmark algorithms. The results show that KE-LODC performs better.
Keywords: healthcare, smart city, linked open data; semantic web; knowledge extraction;
Special Issue on: I3M 2014 New Advances in Simulation and Process Modelling Integrating New Technologies and Methodologies to Enlarge Simulation Capabilities
Combining DEVS and model-checking: concepts and tools for integrating simulation and analysis
by Bernard Zeigler, James Nutaro, Chungman Seo
Abstract: Our objectives here are to discuss the development of a formal framework that exploits the advantages of the Discrete Event System Specification (DEVS) formalism and builds upon recent extensive work on verification combining DEVS and model checking for hybrid systems. The mathematical concepts within the DEVS formalism encompass a broad class of systems that includes multi-agent discrete event components combined with continuous components such as timed automata, hybrid automata, and systems described by constrained differential equations. Moreover, DEVS offers the ability, via mathematical transformations called system morphisms, to map a system expressed in a formalism suitable for analysis (e.g., timed automata or hybrid automata) into the DEVS formalism for the purpose of simulation. Conversely, it is also possible to go from DEVS to formalism suitable for analysis for the purposes of model checking, symbolic extraction of test cases, reachability, among other analysis tasks. We discuss a probabilistic extension of the FD-DEVS formalism that enables a set of model classes and tools derived from Markov-type models. The MS4 modeling environment provides a suite of tools that support this extension, called FP-DEVS. In this paper we describe these tools and concepts underlying them. We also provide examples of application of these concepts and discuss the open opportunities for research in this direction.
Keywords: DEVS , model-checking, verification, simulation, modeling and simulation tools, Markov models
Application of mobile devices within distributed simulation-based decision making
by Josef Brozek, Martin Jakes
Abstract: As a consequence of the development of the market with information technology, where users are increasingly inclined towards mobile devices at the expense of conventional stand-alone devices, increasing user literacy in the use of smartphones and tablets, and the increasing computing performance of mobile devices, a study has been created that addresses the potential of using mobile devices in a distributed simulation. The study also focuses on the possibility of applying the various technologies and architectures in a context of using mobile devices in simulation. This article provides overview information about the study itself, but it is strongly focused on technologies and paradigms that were identified as highly perspective. The paper also explains fundamental themes so that the readers could also apply the information in their home environment. Part of the work is an extensive case study carried out in collaboration with a commercial entity.
Keywords: simulation, tablet, smartphone, mobile device, distributed simulation, heterogenic simulation, HLA, simulation-based decision making, decision making.
Integrated and collaborative process-based simulation framework for construction project planning
by Ali Ismail, Raimar Scherer, Yaseen Srewil
Abstract: This paper presents an integrated process-based Construction Simulation Toolkit (CST) and a collaboration platform named ProSIM to support planning of construction projects using simulation techniques. The data integration between the simulation model and the project information is based on Building Information Modelling (BIM) and multi-model data exchange approaches. CST aims to support planning of production and logistic operations of construction projects through rapid development of simulation models and efficient integration of simulation input data from various data models and real-time data, and ProSIM is a web-based portal enabling collaboration among the simulation study and project planning teams. This paper gives an overview about the whole simulation framework and focuses on the integration of simulation input data for the basic project data, namely: a product model based on IFC standards, process models based on BPMN notation, planning and resources data, and real-time data fusion technology. It discusses and presents the latest research work and the prototype implementation through study cases.
Keywords: construction project planning, simulation, process management; simulation data integration; reference process modelling, collaborative planning, RFID, CPS.
Fluid flow simulation over complex shape objects using image processing to achieve mesh generation
by Khaoula Lassoued, Tonino Sophy, Julien Jouanguy, Luis Le-Moyne
Abstract: In the domain of flow simulation, avoiding the manual conception and numerisation of the domain can lead to the saving of a certain amount of time. Some processes, using heavy devices such as LASER metrology, allow the numerical reconstruction of a real object. The aim of this paper is to propose a more simple tool requiring a commercial digital camera (such as a smartphone), to transform a digital picture into a ready-to-use mesh. Besides simplicity, the tool has to be precise enough to bring accurate simulation results. Then, image processing and object detection and reconstruction are used to generate a 2D mesh that can be integrated in a finite-volume transient CFD simulation. Cars and airfoils are chosen as objects, and the DNS fluid flow Gerris solver performs the simulations. After a validation on a circular shape object, simulations, conducted at different Reynolds number, provide accurate results plotting the Von Karman alley regime.
Keywords: flow simulation; bi-dimensional; object recognition; complex shape; car flow; circular cylinder; square cylinder; airfoil; image processing; OpenCv; mesh generation; Gerris.
Design and implementation of communication patterns using parallel objects
by Mario Rossainz Lopez, Manuel Capel Tuñon
Abstract: Within an environment of parallel objects, an approach of structured parallel programming with the paradigm of object orientation is presented here. The proposal includes a programming method based on High Level Parallel Compositions or HLPCs (CPANs in Spanish). C++ classes and CPANs are syntactically alike and differ in concurrency mechanisms. Different parallel programming patterns, synchronisation operations and new constructs such as futures have been discussed throughout the paper. To achieve software reusability, a series of predefined patterns that use object-oriented programming concepts have been presented. Concurrency related constraints on process synchronisation are set by only resorting to maxpar, mutex, sync primitives in the application code. By means of the method application, the implementation of commonly used parallel communication patterns is explained to finally present a library of classes for C++ applications that use POSIX threads.
Keywords: high level parallel composition, parallel objects; communication patterns; structured parallel programming; high performance computing.
Enriching the formalism of coloured Petri nets for modelling alternative structural configurations of a discrete event system: disjunctive coloured Petri nets
by Juan Ignacio Latorre-Biel, Mercedes Perez de la Parte, Emilio Jimenez-Macias
Abstract: Discrete event systems (DES) provide an approximate approach for dealing with certain types of real systems. DES have been extensively and successfully used in modelling and simulation of technological systems and processes. In this field, Coloured Petri Nets (CPN) have arisen as a practical formalism for modelling DES, widely used thanks to the ease of their application, as well as the compactness of the resulting models, and the availability of computer software, ready to be used for modelling, simulation, theoretical analysis, as well as performance evaluation. This paper derives, from the CPN, a formalism focused on modelling DES with alternative structural configurations. That is to say, systems with freedom degrees in their structure, which should be solved by decision-makers, deducing the best configuration among a set of alternative structures.
Keywords: disjunctive coloured Petri nets; alternative structural configurations; manufacturing facility; design; decision support systems; discrete event systems
Special Issue on: I3M 2014 Modelling and Applied Simulation for the 3rd Millennium Enhancements in Traditional Approaches and Moving Towards Simulation as Service
Competencies acquisition with simulation application in th ecourse 'Construction planning and controlling'
by Ailton Freire, Caroline Cavalheiro, Antônio Jungles
Abstract: This paper presents a report of the table simulation use to develop the students competencies in the course of Construction Planning and Controlling on a college course of Civil Engineering at a Brazilian university. The theories used are directly linked to teaching for competence, the methodology of table simulation, and planning and controlling of construction techniques. Two groups of students were compared in the study. One of the groups was submitted to the traditional teaching methodology and the other group to the teaching for competence methodology; the second method was based on the table simulation technique. The results achieved are: a) identifying and developing the civil engineers competencies specialised in construction programming and controlling, and b) confirmation that learning is more effective once it is applied in student education with exercises and techniques of simulation of professional practice.
Keywords: simulation, table simulation, competence, construction scheduling, skills, problem-based learning.
A simulation-based method for inventory ownership planning of aircraft spare engines and parts
by Jose Ramirez-Hernandez, Steven Oakley, Mei Zhang, Alejandro Scalise
Abstract: The planning of spare engines and engine parts is a challenging and critical task for airlines to seamlessly support flying and engine repair operations. Engines are expensive and critical assets that make this problem important from the financial and operational perspectives. Thus, this paper presents a simulation-based method for planning the required spare ownership levels for engine spares and engine parts. The models presented are used in single and multi-location settings and can be used to provide estimations of the minimum spare ownership required to meet given service levels and performance metrics based on out-of-service aircraft events. Two levels of modelling are provided: a higher level where the repairable items are the engines as a whole, and a lower level that focuses on the repair of the individual engine components. Two simulation studies with actual industry data are also presented to illustrate the application of our models.
Keywords: supply chain; inventory planning; simulation; spare engine and parts planning.
Heterogenous model ensembles for short term prediction of stock market trends
by Stephan Winkler, Susanne Schaller, Gabriel Kronberger, Michael Affenzeller, Bonifacio Castaño, Sergio Luengo
Abstract: We here discuss the identification of heterogeneous ensembles for short term prediction of trends in stock markets. The goal is to predict trends (uptrend, sideway trend, or downtrend) for the next day, the next week, and the next month. A sliding window approach is used; model ensembles are iteratively learned and tested on subsequent data points. We have applied several machine learning approaches, the models produced using these methods have been combined to heterogeneous model ensembles. The final estimation for each sample is calculated via majority voting, and the confidence in the final estimation is calculated as the relative ratio of a sample's majority vote. We use a confidence threshold that specifies the minimum confidence level that has to be reached. In the empirical section we discuss results achieved using data of the Spanish stock market recorded from 2003 to 2013.
Keywords: financial data analysis, ensemble modelling, trend classification, machine learning
An interoperable and immersive simulation as training and procedure design support system in car terminals
by Letizia Nicoletti, Antonio Padovano
Abstract: Designing efficient operational procedures and training operators to be responsive and consistent with them in a timely manner is critical in many industrial sectors. Indeed, companies strive to achieve increased efficiency in the procedure design process and look for innovative valuable and cost-effective approaches that push operators to reach the plateau of such procedures learning curve as quickly as possible in order to save money and time. In particular, port terminals, and car terminals specifically, are complex systems because many operations involving coordination problems usually take place. In car terminals, complex procedures must be strictly respected and are regulated by security, reliability, optimisation and synchronisation protocols that each worker has to know and comply with when performing his tasks. Therefore, a consistent and replicable simulation-based framework is proposed for training operators in car terminals in order to improve operators efficiency and enhance the effectiveness of both training activities and procedure design processes. Cutting-edge technologies are integrated with the proposed system, thus providing the end-user with a full-immersive experience and promoting a human-in-the-loop and hardware-in-the-loop approach.
Keywords: marine ports, car terminal, training, simulation, design support
Towards energy efficiency of interdependent urban networks
by Michele Minichino
Abstract: Modernised urban networks will constitute the backbone of smart cities. The modernisation process of urban networks is a long way from being realised, and an extensive use of comprehension, and of models at an adequate level of granularity, are needed. The paper proposes a cross-domain methodology to represent and evaluate the energy efficiency of interdependent urban smart grids and gas and water networks. Models use domain simulators to faithfully represent each physical network, and transversal simulators, to represent together the three interdependent physical networks and to compute energy efficiency indicators. Models built by domain simulators are used to validate models built by transversal simulators. An actual smart grid connected to photovoltaic plants of different size and location is then modelled and its efficiency indicators are analysed and discussed. The grid model will be then interconnected with basic gas and network models to investigate the impact of interdependency on the grid efficiency indicators.
Keywords: smart city, smart grid, gas network, water network, SCADA, energy efficiency, interdependency, model
Special Issue on: Simulation Modelling and Optimisation of Large-scale Systems
An iterative parametric estimation method for Hammerstein large-scale systems: a simulation study of hydraulic process
by Elloumi Mourad, Kamoun Samira
Abstract: This paper aims at developing an iterative method that permits to estimate the parameters of Single-Input Single-Output (SISO) large-scale nonlinear systems, described by Hammerstein mathematical models. We particularly focus on the dynamic large-scale nonlinear systems, which are made up of several interconnected nonlinear monovariable subsystems. Each subsystem can operate in a stochastic environment and is described by a discrete-time Hammerstein mathematical model with known structure variables (order, delay) and unknown time-varying parameters. The problem formulation is achieved based on the prediction error method and the least-squares techniques. The convergence analysis of the recursive algorithm is provided using the differential equation approach and its performance is illustrated by treating two simulation examples.
Keywords: large-scale nonlinear systems; Stochastic systems; mathematical modelling; Hammerstein models; parametric estimation; convergence analysis; simulation; hydraulic process.
Hybrid clustering technique of PCA-SM-GHSOM for abnormal and normal classification with quarterly financial ratios of the listed TCM company sector
by Ruicheng Yang
Abstract: By combining principal component analysis (PCA) and the similarity matching (SM) method with growing hierarchical self-organising map (GHSOM), this paper provides a hybrid technique PCA-SM-GHSOM for clustering the quarterly financial data into normal and abnormal groups. For evaluating the performance of this hybrid method, we give some empirical analysis for the listed traditional Chinese medicine (TCM) companies in China. Three stages are proposed for the clustering experiment. First, we use the PCA method to reduce the high dimensions of financial ratios into low dimensions. Secondly, we adopt the cosine similarity computation method to measure the similarity between the considered company and the other companies of the same TCM sector. According to the similarity values, we choose the three best matching companies, and further get the deviation dataset of the considered company. Finally, we put the deviation dataset into the GHSOM system and derive the clustering results. Furthermore, we derive the empirical clustering results with other different techniques that are single GHOM, combination of PCA-GHSOM, combination of SM, and GHSOM. By comparing these experiment results with that of the hybrid technique PCA-SM-GHSOM, we find that the proposed hybrid technique can improve greatly the accuracy for clustering the data into normal and abnormal groups.
Keywords: PCA-SM-GHSOM; cosine similarity; financial ratios; TCM
Reward processes and performance simulation in supermarket models with different servers
by Quan-Lin Li, Feifei Yang, Na Li
Abstract: Supermarket models with different servers are key in modelling resource
management of stochastic networks, such as computer networks, manufacturing systems, transportation networks, and healthcare systems. The different servers always make analysis of such a supermarket model more interesting, difficult and challenging. This paper provides a novel method for analysing the supermarket models with different servers through a multi-dimensional continuous-time Markov reward process. First, some utility functions are constructed for designing the routine selection mechanism according to the queue lengths, the service rates, and the probability of individual preference. Second, using the state jump points of the continuous-time Markov reward process, some segmented stochastic integrals of the random reward function are established by means of an event-driven technique. Based on this, the mean of the random reward function in a finite time interval is computed, and the mean of the discounted random reward function in an infinite time interval can also be calculated. Finally, some simulation experiments are given to indicate how the expected queue length of each server depends on some key parameters of this supermarket model.
Keywords: supermarket model; routine selection mechanism; Markov reward process; stochastic integral; event-driven technique.
Optimization of Recommended Speed Profile for Train Operation Based on Ant Colony Algorithm
by Fang Cao, Liqian Fan, Bworen Ke, Tao Tang
Abstract: An automatic train operation (ATO) system generally consists of the generation of recommended speed profile and the speed tracking strategy. It determines the tracked trajectory and the energy consumption of trains during the trip. Therefore, the optimisation of recommended speed profile and the ATO tracking strategy are regarded as two important means to achieve energy-efficient train operation between the successive stations. With considering the ATO tracking strategy, an optimisation method of the recommended speed profile is proposed in this paper. Based on the approximate calculation, a discrete combination optimisation model is formulated and a modified MAX-MIN ant system (MMAS) is taken as the core algorithm. With the integration speed tracking strategy, this method achieves the recommended speed profile with optimised energy consumption and a perfect running punctuality along the actual tracked trajectory. The computation time of the algorithm is shorter and the switching times of operation during the cruising phase are reduced by integrating the drivers' experience, which also reduces the energy consumption of train running between stations. The simulation results of a case study based on the Beijing Subway verify the effectiveness of the proposed method, which has a good performance on energy-efficient train operation.
Keywords: recommended speed profile; optimisation model; ant colony algorithm; energy-efficient train operation; simulation.
Shipment policy optimisation in a return supply chain for online retailers via stochastic discrete event simulation
by Haobin Li, Giulia Pedrielli
Abstract: Limiting the costs for return of products is a key competing factor for online retailers. In fact, free returns are considered an important performance to the customer. However, to guarantee free returns, the company has to precisely estimate the costs implied in the return supply chain. In this paper, we specifically look at the problem of international online retailers that have to manage the shipment of return products between different countries. In this scope, we first formalise the return process and we propose a two-parameters strategy to manage the shipment of returned products across countries. In order to solve the problem, we propose to use simulation-optimisation, resulting in a general solution approach not limited by stringent assumptions.
Keywords: simulation optimisation; discrete event simulation; return supply chain; online retailer; shipment policy
Multiobjective optimal computing budget allocation for multiobjective particle swarm optimisation with particledependent weights
by Yue Liu
Abstract: In this paper, we develop a multi-objective optimal computing budget allocation method with multiple weights (MOCBAmw) assigned to each particle in MPSOws (multi-objective particle swarm optimisation based on weighted scalarising functions) algorithm in the stochastic environment. By intelligently allocating computing budget among all particles instead of simple equal allocation (EA), we are able to improve the probability of correctly selecting the global best designs under limited computing budget. Improvement of correct leading particles identification in each generation of the MPSOws procedure helps to facilitate the convergence of the swarm to the Pareto front in the stochastic environment. Testing results from bi-objective ZDT problems and tri-objective DTLZ problems have shown that MOCBAmw achieves a better convergence rate and a higher hypervolume than EA under the same noise setting.
Keywords: multi-objective simulation optimisation; stochastic simulation optimisation; particle swarm optimisation; optimal computing budget allocation.
A particle filtering-based estimation of distribution algorithm for multi-objective optimisation
by Xiaoran Shi, Nurcin Celik
Abstract: A novel particle filtering-based estimation of distribution algorithm (EDA) is proposed to address multi-objective optimisation problems. Specifically, the particles drawn from a sampling distribution are considered as the candidate solutions. This sampling distribution is computed recursively based on the performance of the prior particle set and the newly arrived observations. As the iteration progresses, the distribution function gradually concentrates on the promising region(s) of the solution space, indicating higher probabilities to obtain solutions with good performances in terms of the objective values. In order to validate the performance of the proposed algorithm, a case study of an economic and environmental load dispatch (EELD) is conducted where the bi-objective EELD optimisation problem is solved via the proposed algorithm, and the performance of the proposed algorithm is benchmarked against several algorithms studied in the literature. Experimental results have revealed that the proposed algorithm produces very promising results against those in the literature.
Keywords: particle filtering, estimation of distribution algorithm, multi-objective optimisation
Application of multi-fidelity simulation modelling to integrated circuit packaging
by Liam Hsieh, Edward Huang, Si Zhang, Kuo-Hao Chang, Chun-Hung Chen
Abstract: In semiconductor manufacturing, time-to-market is critical to maintain a competitive advantage through achieving customer satisfaction. Inefficient ways of using production resources will lead to a long cycle time. Therefore, machine allocation becomes an essential production decision in many practical manufacturing systems, especially for integrated circuit (IC) packaging. IC packaging is the process of encasing the finished die in a package in order to prevent corrosion and physical damage. Advanced IC packaging techniques add even more complexity into the production system, so reliable average cycle time of this complex system becomes difficult to be obtained. We propose a new simulation optimisation framework with multi-fidelity models to study an IC packaging case of the machine allocation problem to pursue a minimum average cycle time. This framework consists of two methodologies: ordinal transformation (OT) and optimal sampling (OS). The OT first employs the low-fidelity model to fast observe all designs, and extracts insightful information from this model by transform the original design space into an ordinal space. It follows that OS efficiently allocates the computing budget for searching the best design via high-fidelity simulations. An empirical study based on real data was conducted to validate the practical viability of the proposed framework.
Keywords: machine allocation; semiconductor manufacturing; multi-fidelity simulation; simulation optimisation; ordinal transformation; optimal sampling.
Renewable-load matching dispatch for isolated power systems with intermittent renewable sources
by Ying Shen, Qianchuan Zhao, Mingyang Li
Abstract: This paper proposes a renewable-load matching approach for dispatching generation resources in power systems with high renewable power penetrations. In order to use the capability of renewable resources to follow the load variations, the proposed matching approach is to restrict the output of renewable generators by a load-related bound in each dispatch time period. The dispatch problem is formulated to minimise the system cost comprising fuel, emission, and regulation costs, as well as renewable power curtailment penalty. Compared with the traditional approach of treating renewable resources as negative loads, the proposed matching approach can significantly reduce the system cost by including the dynamic control of renewable power output. Moreover, the multi-objective function provides a way to study the tradeoff among different costs in power systems with renewable resources. The solution is obtained by transforming the optimisation problem into its equivalent form and using local search algorithms. Simulations are implemented on a specific isolated power system with four generators to demonstrate the advantage of the proposed approach.
Keywords: intermittent renewable resources, energy dispatch, isolated power system, wind power, uncertainty, optimisation, local search, sensitivity analysis.
A simulation model for outpatient appointment scheduling with patient unpunctuality
by Li Luo, Ying Zhou, Bernard T. Han, Yingkang Shi, Qiyun Song, Xiaoli He, Zhaoxia Guo
Abstract: This paper investigates the appointment system of an outpatient department in a large hospital in China in order to reduce the long waiting times for patients. Through a sensitivity analysis using actual data, the study shows that patient unpunctuality and doctor consultation time have significant impacts on the patient waiting time. To facilitate the existing practice without making strong assumptions, a simulation model is developed to identify proper appointment rules for appointment scheduling with severe patient unpunctuality. Specifically, four outpatient environments, characterised by a preset appointment time interval with variable doctor consultation times, were simulated and 100 scenarios were run for each environment to identify a proper appointment rule that has the shortest patient average waiting time (PAWT). Results indicate that PAWT is consistently shorter for environments when patients are punctual and, moreover, is barely affected by the length of appointment time interval. However, for environments with patient unpunctuality, a proper appointment rule could potentially reduce PAWT by up to 34% (i.e., reducing the appointment time interval from 1.0 hour to 0.5 hour). The developed simulation model may serve as an efficient tool to enhance outpatient appointment scheduling with patient unpunctuality. Possible extensions to the presented model are also discussed.
Keywords: simulation; outpatient appointment; unpunctuality; scheduling; patient waiting time