Discrete event simulation tool for analysis of qualitative models of continuous processing systems

An artificial intelligence design and qualitative modeling tool is disclosed for creating computer models and simulating continuous activities, functions, and/or behavior using developed discrete event techniques. Conveniently, the tool is organized in four modules: library design module, model construction module, simulation module, and experimentation and analysis. The library design module supports the building of library knowledge including component classes and elements pertinent to a particular domain of continuous activities, functions, and behavior being modeled. The continuous behavior is defined discretely with respect to invocation statements, effect statements, and time delays. The functionality of the components is defined in terms of variable cluster instances, independent processes, and modes, further defined in terms of mode transition processes and mode dependent processes. Model construction utilizes the hierarchy of libraries and connects them with appropriate relations. The simulation executes a specialized initialization routine and executes events in a manner that includes selective inherency of characteristics through a time and event schema until the event queue in the simulator is emptied. The experimentation and analysis module supports analysis through the generation of appropriate log files and graphics developments and includes the ability of log file comparisons

Solving Combinatorial Optimization Problems Using Genetic Algorithms and Ant Colony Optimization

This dissertation presents metaheuristic approaches in the areas of genetic algorithms and ant colony optimization to combinatorial optimization problems. Ant colony optimization for the split delivery vehicle routing problem An Ant Colony Optimization (ACO) based approach is presented to solve the Split Delivery Vehicle Routing Problem (SDVRP). SDVRP is a relaxation of the Capacitated Vehicle Routing Problem (CVRP) wherein a customer can be visited by more than one vehicle. The proposed ACO based algorithm is tested on benchmark problems previously published in the literature. The results indicate that the ACO based approach is competitive in both solution quality and solution time. In some instances, the ACO method achieves the best known results to date for the benchmark problems. Hybrid genetic algorithm for the split delivery vehicle routing problem (SDVRP) The Vehicle Routing Problem (VRP) is a combinatory optimization problem in the field of transportation and logistics. There are various variants of VRP which have been developed of the years; one of which is the Split Delivery Vehicle Routing Problem (SDVRP). The SDVRP allows customers to be assigned to multiple routes. A hybrid genetic algorithm comprising a combination of ant colony optimization, genetic algorithm, and heuristics is proposed and tested on benchmark SDVRP test problems. Genetic algorithm approach to solve the hospital physician scheduling problem Emergency departments have repeating 24-hour cycles of non-stationary Poisson arrivals and high levels of service time variation. The problem is to find a shift schedule that considers queuing effects and minimizes average patient waiting time and maximizes physicians’ shift preference subject to constraints on shift start times, shift durations and total physician hours available per day. An approach that utilizes a genetic algorithm and discrete event simulation to solve the physician scheduling problem in a hospital is proposed. The approach is tested on real world datasets for physician schedules

A survey of simulation techniques in commerce and defence

Despite the developments in Modelling and Simulation (M&S) tools and techniques over the past years, there has been a gap in the M&S research and practice in healthcare on developing a toolkit to assist the modellers and simulation practitioners with selecting an appropriate set of techniques. This study is a preliminary step towards this goal. This paper presents some results from a systematic literature survey on applications of M&S in the commerce and defence domains that could inspire some improvements in the healthcare. Interim results show that in the commercial sector Discrete-Event Simulation (DES) has been the most widely used technique with System Dynamics (SD) in second place. However in the defence sector, SD has gained relatively more attention. SD has been found quite useful for qualitative and soft factors analysis. From both the surveys it becomes clear that there is a growing trend towards using hybrid M&S approaches

BIM Integrated and Reference Process-based Simulation Method for Construction Project Planning

Die Verwendung von Simulationen zur Unterstützung traditioneller Planungsverfahren für Bauprojekte hat viele Vorteile, die in verschiedenen akademischen Forschungen vorgestellt wurden. Viele Anwendungen haben erfolgreich das Potenzial der Simulationsmethode zur Verbesserung der Qualität der Projektplanung demonstriert. Doch eine breite Anwendung der Simulationsmethoden zur Unterstützung der Planung von Bauprojekten konnte sich in der Praxis bis zum jetzigen Zeitpunkt nicht durchsetzen. Aufgrund einiger großer Hindernisse und Herausforderungen ist der Einsatz im Vergleich zu anderen Branchen noch sehr begrenzt. Die Komplexität sowie die dynamischen Wechselprozesse der unterschiedlichen Bauvorhaben stellen die erste Herausforderung dar.Die Anforderungen machen es sehr schwierig die verschieden Situationen realistisch zu modellieren und das Verhalten von Bauprozessen und die Interaktion mit den zugehörigen Ressourcen für reale Bauvorhaben darzustellen. Das ist einer der Gründe für den Mangel an speziellen Simulationswerkzeugen in der Bauprojektplanung. Die zweite Herausforderung besteht in der großen Menge an Projektinformationen, die in das Simulationsmodell integriert und während des gesamten Lebenszyklus des Projekts angepasst werden müssen. Die Erstellung von Simulationsmodellen, Simulationsszenarien sowie die Analyse und Verifizierung der Simulationsergebnisse ist langwierig. Ad-hoc Simulation sind daher nicht möglich. Zur Erstellung zuverlässiger Simulationsmodelle sind daher umfangreiche Ressourcen und Mitarbeiter mit speziellen Fachwissen erforderlich. Die vorgestellten Herausforderungen verhindern die breite Anwendung der Simulationsmethode zur Unterstützung der Bauprojektplanung und das Einsetzen der Software als wesentlicher Bestandteil des Arbeitsablaufes für die Bauplanung in der Praxis. Die Forschungsarbeit in dieser Arbeit befasst sich mit diesen Herausforderungen durch die Entwicklung eines Ansatzes sowie einer Plattform für die schnelle Aufstellung von Simulationsmodellen für Bauprojekte. Das Hauptziel dieser Forschung ist die Entwicklung eines integrierten und referenzmodellbasierten BIM Simulationsansatz zur Unterstützung der Planung von Bauprojekten und die Möglichkeit der Zusammenarbeit aller am Planungs- und Simulationsprozess beteiligten Akteure. Die erste Herausforderung wird durch die Einführung eines RPM-Konzepts (Reference Process Model) durch die Modellierung von Konstruktionsprozessen unter Verwendung von Business Process Modeling and Notation (BPMN) angegangen. Der Vorteil der RPM Modelle ist das sie bearbeitet und modifiziert können und dass sie automatisch als einsatzbereite Module in Simulationsmodelle umgewandelt werden können. Die RPM-Modelle enthalten auch Informationen zu Ressourcenanforderungen und andere verwandte Informationen für verschiedene Baubereiche mit unterschiedlichen Detaillierungsgraden. Die Verwendung von BPMN hat den Vorteil, dass die Simulationsmodellierung für das Projektteam, einschließlich derjenigen, die sich nicht mit der Simulation auskennen, flexibler, interoperabler und verständlicher ist. Bei diesem Ansatz ist die Modellierung von Referenzprozessmodellen vollständig von den Simulationskernkomponenten getrennt, um das Simulations-Toolkit generisch und erweiterbar für verschiedenste Konstruktionsbereiche wie Gebäude und Brücken. Der vorgestellte Forschungsansatz unterstützt die kontinuierliche Anwendung von Simulationsmodellen während des gesamten Projektlebenszyklus. Die Simulationsmodelle, die zur Unterstützung der Planung in der frühen Entwurfsphase erstellt werden, können von Simulationsexperten während der gesamten Planungs- und Bauphase weiter ausgebaut und aktualisiert werden. Die zweite Herausforderung wird durch die direkte Integration der Building Information Modeling (BIM) -Methode in die Simulationsmodellierung auf der Grundlage des Industry Foundation Classes-IFC (ISO 16739) , dem am häufigsten verwendeten BIM-Austauschformat, angegangen. Da die BIM-Modelle einen wichtigen Teil der Eingabeinformationen von Simulationsmodellen enthalten, können sie als Grundlage für die Visualisierung von Ergebnissen in Form von 4D-BIM-Modellen verwendet werden. Diese Integration ermöglicht die schnelle und automatische Filterung und Extraktion sowie die Umwandlung notwendiger Informationen aus BIM Entwurf-Modellen. Um die Erstellung detaillierter Projektmodelle zu beschleunigen, wurde eine spezielle Methode für die halbautomatische Top-Down-Detaillierung von Projektstammmodelle entwickelt, die notwendige Eingangsdaten für die Simulationsmodelle sind. Diese Methode bietet den Vorteil, dass Konstruktionsalternativen mit minimalen Änderungen am Simulationsmodell untersucht werden können. Der entwickelte Ansatz wurde als Software- Prototyp in Form eines modularen Construction Simulation Toolkit (CST) basierend auf der Discrete Event Simulation (DES)- Methode und eines Collaboration- Webportals (ProSIM) zum Verwalten von Simulationsmodellen implementiert. Die so eingebettete Simulation ermöglicht mit minimalen Änderungen die Bewertung von Entwurfsalternativen und Konstruktionsmethoden auf den Bauablauf. Produktions- und Logistiksvorgänge können gleichzeitig in einer einheitlichen Umgebung simuliert werden und berücksichtigen die gemeinsam genutzten Ressourcen und die Interaktion zwischen Produktions- und Logistikaktivitäten. Es berücksichtigt auch die Änderungen im Baustellenlayout während der Konstruktionsphase. Die Verifizierung und Validierung des vorgeschlagenen Ansatzes wird durch verschiedene hypothetische und reale Bauprojekten durchgeführt.:1 Introduction: motivation, problem statement and objectives 1.1 Motivation 1.2 Problem statement 1.3 Objectives 1.4 Thesis Structure 2 Definitions, Related work and background information 2.1 Simulation definition 2.2 Simulation system definition 2.3 Discrete Event Simulation 2.5 How simulation works 2.6 Workflow of simulation study 2.7 Related work 2.8 Traditional construction planning methods 2.8.1 Gantt chart 2.8.2 Critical Path Method (CPM) 2.8.3 Linear scheduling method/Location-based scheduling 2.9 Business Process Model and Notation 2.10Workflow patterns 2.10.1 Supported Control Flow Patterns 3 Reference Process-based Simulation Approach 3.1 Reference Process-based simulation approach 3.2 Reference Process Models 3.3 Reference process model for single task 3.4 Reference process models for complex activities 3.5 Process Pool 3.6 Top-down automatic detailing of project schedules 3.7 Simulation model formalism 3.8 Fundamental design concepts and application scope 4 Data Integration between simulation and construction Project models 4.1 Data integration between BIM models and simulation models 4.1.1 Transformation of IFC models to Graph models 4.1.2 Checking BIM model quality 4.1.3 Filtering of BIM models 4.1.4 Semantic enrichment of BIM models 4.1.5 Reference process models and BIM models 4.2 Reference Process Models and resources models 4.3 Process models and productivity factors 5 Construction Simulation Toolkit 5.1 System architecture and implementation 5.2 Basic steps to create a CST simulation model 5.3 CST Simulation components 5.3.1 Input components 5.3.2 Process components 5.3.3 Output components 5.3.4 Logistic components 5.3.5 Collaboration platform ProSIM 6 Case Studies and Validation 6.1 Verification and Validation of Simulation Models 6.2 Verification and validation techniques for simulation models 6.3 Case study 1: generic planning model 6.4 Case study 2: high rise building 6.4.1 Scenario I: effect of changing number of workers on structural work duration 6.4.2 Scenario II: simulation of structural work on operation level 6.4.3 Scenario III: automatic generation of detailed project schedule 6.5 Case study 3: airport terminal building 6.5.1 Multimodel Container 6.5.2 Scenario I: automatic generation of detailed project schedule 6.5.3 Scenario II: Find the minimal project duration 6.5.4 Scenario III: construction work for a single floor 7 Conclusions and Future Research 7.1 Conclusions 7.2 Outlook of the possible future research topics 7.2.1 Integration with real data collecting 7.2.2 Multi-criteria optimisation 7.2.3 Extend the control-flow and resource patterns 7.2.4 Consideration of further structure domains 7.2.5 Considering of space allocation and space conflicts 8 Appendix - Scripts 9 Appendix B - Reference Process Models 9.1 Reference Process Models for structural work 9.1.1 Wall 9.1.2 Roof 9.1.3 Foundations 9.1.4 Concrete work 9.1.5 Top-Down RPMs for structural work in a work section 10 Appendix E 10.1 Basic elements of simulation models in Plant Simulation 10.2 Material Flow Objects 11 ReferencesUsing simulation to support construction project planning has many advantages, which have been presented in various academic researches. Many applications have successfully demonstrated the potential of using simulation to improve the quality of construction project planning. However, the wide adoption of simulation has not been achieved in practice yet. It still has very limited use compared with other industries due to some major obstacles and challenges. The first challenge is the complexity of construction processes and projects planning methods, which make it very difficult to develop realistic simulation models of construction processes and represent their dynamic behavior and the interaction with project resources. This led to lack of special simulation tools for construction project planning. The second challenge is the huge amount of project information that has to be integrated into the simulation model and to be maintained throughout the design, planning and construction phases. The preparation of ad-hoc simulation models and setting up different scenarios and verification of simulation results usually takes a long time. Therefore, creating reliable simulation models requires extensive resources with advanced skills. The presented challenges prevent the wide application of simulation techniques to support and improve construction project planning and adopt it as an essential part of the construction planning workflow in practice. The research work in this thesis addresses these challenges by developing an approach and platform for rapid development of simulation models for construction projects. The main objective of this research is to develop a BIM integrated and reference process-based simulation approach to support planning of construction projects and to enable collaboration among all actors involved in the planning and simulation process. The first challenge has been addressed through the development of a construction simulation toolkit and the Reference Process Model (RPM) method for modelling construction processes for production and logistics using Business Process Modelling and Notation (BPMN). The RPM models are easy to understood also by non-experts and they can be transformed automatically into simulation models as ready-to-use modules. They describe the workflow and logic of construction processes and include information about duration, resource requirements and other related information for different construction domains with different levels of details. The use of BPMN has many advantages. It enables the understanding of how simulation models work by project teams, including those who are not experts in simulation. In this approach, the modelling of Reference Process Models is totally separated from the simulation core components. In this way, the simulation toolkit is generic and extendable for various construction types such as buildings, bridges and different construction domains such as structural work and indoor operations. The presented approach supports continuous adoption of simulation models throughout the whole project life cycle. The simulation model which supports project planning in the early design phase can be continuously extended with more detailed RPMs and updated information through the planning and construction phases. The second challenge has been addressed by supporting direct integration of Building Information Modelling (BIM) method with the simulation modelling based on the Industry Foundation Classes IFC (ISO 16739) standard, which is the most common and only ISO standard used for exchanging BIM models. As the BIM models contain the biggest part of the input information of simulation models and they can be used for effective visualization of results in the form of animated 4D BIM models. The integration between BIM and simulation enables fast and semi-automatic filtering, extraction and transformation of the necessary information from BIM models for both design and construction site models. In addition, a special top-down semi-automatic detailing method was developed in order to accelerate the process of preparing detailed project schedules, which are essential input data for the simulation models and hence reduce the time and efforts needed to create simulation models. The developed approach has been implemented as a software prototype in the form of a modular Construction Simulation Toolkit (CST) based on the Discrete Event Simulation (DES) method and an online collaboration web portal 'ProSIM' for managing simulation models. The collaboration portal helps to overcome the problem of huge information and make simulation models accessible for non simulation experts. Simulation models created by CST toolkit facilitate the evaluation of design alternatives and construction methods with minimal changes in the simulation model. Both production and logistic operations can be simulated at the same time in a unified environment and take into account the shared resources and the interaction between production and logistic activities. It also takes into account the dynamic nature of construction projects and hence the changes in the construction site layout during the construction phase. The verification and validation of the proposed approach is carried out through various academic and real construction project case studies.:1 Introduction: motivation, problem statement and objectives 1.1 Motivation 1.2 Problem statement 1.3 Objectives 1.4 Thesis Structure 2 Definitions, Related work and background information 2.1 Simulation definition 2.2 Simulation system definition 2.3 Discrete Event Simulation 2.5 How simulation works 2.6 Workflow of simulation study 2.7 Related work 2.8 Traditional construction planning methods 2.8.1 Gantt chart 2.8.2 Critical Path Method (CPM) 2.8.3 Linear scheduling method/Location-based scheduling 2.9 Business Process Model and Notation 2.10Workflow patterns 2.10.1 Supported Control Flow Patterns 3 Reference Process-based Simulation Approach 3.1 Reference Process-based simulation approach 3.2 Reference Process Models 3.3 Reference process model for single task 3.4 Reference process models for complex activities 3.5 Process Pool 3.6 Top-down automatic detailing of project schedules 3.7 Simulation model formalism 3.8 Fundamental design concepts and application scope 4 Data Integration between simulation and construction Project models 4.1 Data integration between BIM models and simulation models 4.1.1 Transformation of IFC models to Graph models 4.1.2 Checking BIM model quality 4.1.3 Filtering of BIM models 4.1.4 Semantic enrichment of BIM models 4.1.5 Reference process models and BIM models 4.2 Reference Process Models and resources models 4.3 Process models and productivity factors 5 Construction Simulation Toolkit 5.1 System architecture and implementation 5.2 Basic steps to create a CST simulation model 5.3 CST Simulation components 5.3.1 Input components 5.3.2 Process components 5.3.3 Output components 5.3.4 Logistic components 5.3.5 Collaboration platform ProSIM 6 Case Studies and Validation 6.1 Verification and Validation of Simulation Models 6.2 Verification and validation techniques for simulation models 6.3 Case study 1: generic planning model 6.4 Case study 2: high rise building 6.4.1 Scenario I: effect of changing number of workers on structural work duration 6.4.2 Scenario II: simulation of structural work on operation level 6.4.3 Scenario III: automatic generation of detailed project schedule 6.5 Case study 3: airport terminal building 6.5.1 Multimodel Container 6.5.2 Scenario I: automatic generation of detailed project schedule 6.5.3 Scenario II: Find the minimal project duration 6.5.4 Scenario III: construction work for a single floor 7 Conclusions and Future Research 7.1 Conclusions 7.2 Outlook of the possible future research topics 7.2.1 Integration with real data collecting 7.2.2 Multi-criteria optimisation 7.2.3 Extend the control-flow and resource patterns 7.2.4 Consideration of further structure domains 7.2.5 Considering of space allocation and space conflicts 8 Appendix - Scripts 9 Appendix B - Reference Process Models 9.1 Reference Process Models for structural work 9.1.1 Wall 9.1.2 Roof 9.1.3 Foundations 9.1.4 Concrete work 9.1.5 Top-Down RPMs for structural work in a work section 10 Appendix E 10.1 Basic elements of simulation models in Plant Simulation 10.2 Material Flow Objects 11 Reference

Opticap XL Output and Workflow Improvement- Examining Production Line Dedication

Insufficient production capacity and backorder buildup motivated EMD Millipore to examine its Opticap XL filter encapsulation process. Through analyzing this process and interviews with key stakeholders our team confirmed the changeover process as a production bottleneck. One way to potentially reduce changeover time is through line dedication by product characteristics. In this project, we built a discrete-event simulation model to evaluate different dedication scenarios and ultimately recommended dedication by capsule size

Project scheduling under undertainty – survey and research potentials.

The vast majority of the research efforts in project scheduling assume complete information about the scheduling problem to be solved and a static deterministic environment within which the pre-computed baseline schedule will be executed. However, in the real world, project activities are subject to considerable uncertainty, that is gradually resolved during project execution. In this survey we review the fundamental approaches for scheduling under uncertainty: reactive scheduling, stochastic project scheduling, stochastic GERT network scheduling, fuzzy project scheduling, robust (proactive) scheduling and sensitivity analysis. We discuss the potentials of these approaches for scheduling projects under uncertainty.Management; Project management; Robustness; Scheduling; Stability;