EVALUATION OF SIMULATION TECHNIQUES FOR MODELING PROGRESSION OF CONSTRUCTION CLAIMS

2018 ◽  
Vol 5 (1) ◽  
Author(s):  
Mohammad Barakat ◽  
Hiam Khoury ◽  
Mohamed-Asem Abdul-Malak
Keyword(s):  
Construction Projects ◽  
Discrete Event ◽  
Hybrid Approach ◽  
Simulation Models ◽  
Complex Problem ◽  
Weak Links ◽  
Agent Based ◽  
Event Simulation ◽  
Simulation Techniques ◽  
Potential Applicability

The unstructured and dynamic nature of construction projects and the on-site work complexities have been inevitably leading to claims. These evolve according to a staged mechanism set forth in the adopted conditions of contracts. More specifically, claims might progress expeditiously or drag depending on the nature of the applied mechanism and the behavior and interaction among contractual parties. As such, this complex problem of claim progression, which entails a lot of parameters and variables, is addressed in detail in this paper by resorting to three simulation techniques namely: (1) Discrete-Event Simulation (DES), (2) Agent-Based Modeling (ABM), and (3) System Dynamics (SD). The purpose behind this study is two-fold: (1) capturing and visualizing, through three different simulation models, the dynamic and interaction among the different entities as claims are progressing and defining the weak links hindering the efficiency improvement of such a process, and (2) comparing DES, ABM, and SD simulation approaches, using choose-by-advantage technique, and evaluating the advantages and drawbacks of each when studying the progression of claims. Results of all approaches are presented and analyzed followed by a discussion of the effectiveness of each simulation technique and the potential applicability of a hybrid approach in modeling the progression of claims.

Modelling and simulation of a fire department’s response to emergency incidents

2018 ◽  
Author(s):  
Adriano O. Solis ◽  
Jenaro Nosedal-Sánchez ◽  
Ali Asgary ◽  
Francesco Longo ◽  
Beatrice Zaccaro
Keyword(s):  
Simulation Model ◽  
Discrete Event ◽  
Fire Department ◽  
Simulation Models ◽  
Modelling And Simulation ◽  
Fire Departments ◽  
Simulation Experiments ◽  
Agent Based ◽  
Event Simulation ◽  
Principal Elements

"After statistical analysis of the database of a fire department covering eight years of consecutive incident records from January 2009 to December 2016, we developed a modelling and simulation (M&S) approach that could be replicated for fire departments across Canada. Our M&S framework involved two different simulation models running on separate platforms: (i) an Incident Generation Engine, which simulates the ‘arrival’ of emergency incidents, and (ii) a Response Simulation Model. The first model is a discrete event simulation model using CPNTools 4.0, generating inputs for the second model, which is an agent-based simulation model developed using AnyLogic. We discuss the principal elements of the two simulation models, and report on findings from our simulation experiments."

Discrete-event simulation and agent-based modeling in the tasks of the school informatics course

2020 ◽  
Vol 1 (9) ◽  
pp. 4-13
Author(s):  
N. V. Klimina ◽  
I. A. Morozov
Keyword(s):  
Extracurricular Activities ◽  
Discrete Event ◽  
Simulation Models ◽  
Agent Based Modeling ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Event Simulation ◽  
Cellular Environment ◽  
Scope Of Application ◽  
Biological Simulation

In order to study processes and phenomena, it is necessary to create their models. The most interesting and valuable for the analysis of current situations are models that describe processes as if they were happening in reality. These are the so-called simulation models. The scope of application of simulation models is extensive. The most in demand are economic, sociological and biological simulation models. The relevance of simulation is obvious, and it is natural that the theme of simulation is present in the content of the school informatics course. The article provides guidelines for studying the basics of modeling in a school informatics course related to the creation and research of discrete-event and agent-based simulation models. Examples of tasks recommended for consideration in the 9–11th grades at informatics lessons or in extracurricular activities are given, these are task based on the information-cybernetic approach, implemented in the PascalABC environment, and the task using a cellular automaton, implemented in the Cellular environment.

scholarly journals DVCompute Simulator for discrete event simulation

2021 ◽  
Vol 16 (93) ◽  
pp. 93-108
Author(s):  
David E. Sorokin ◽  
Keyword(s):  
Discrete Event Simulation ◽  
Large Scale ◽  
Distributed Simulation ◽  
Discrete Event ◽  
Simulation Models ◽  
General Purpose ◽  
Agent Based Modeling ◽  
Agent Based ◽  
Event Simulation ◽  
Programming Techniques

The author of this article represents his own work DVCompute Simulator, which is a collection of general-purpose programming libraries for discrete event simulation. The aim of the research was to create a set of simulators in the Rust language, efficient in terms of speed of execution, based on a unified approach and destined for different simulation modes. The simulators implement such modes as ordinary sequential simulation, nested simulation and distributed simulation. The article describes that nested simulation is related to Theory of Games, while distributed simulation can be used for running large-scale simulation models on supercomputers. It is shown how these different simulation modes can be implemented based on the single approach that combines many paradigms: the event-oriented paradigm, the process-oriented one, blocks similar to the GPSS language and even partially agent-based modeling. The author's approach is based on using the functional programming techniques, where the simulation model is defined as a composition of computations. The results of testing two modules are provided, where the modules support both the optimistic and conservative methods of distributed simulation.

scholarly journals Distributed Approaches to Supply Chain Simulation

2021 ◽  
Vol 31 (4) ◽  
pp. 1-31
Author(s):  
Navonil Mustafee ◽  
Korina Katsaliaki ◽  
Simon J. E. Taylor
Keyword(s):  
Supply Chain ◽  
State Of The Art ◽  
Discrete Event ◽  
Simulation Models ◽  
Event Simulation ◽  
Distributed Decision Making ◽  
Simulation Techniques ◽  
Current State ◽  
Trade Offs ◽  
Supply Chain Simulation

The field of Supply Chain Management (SCM ) is experiencing rapid strides in the use of Industry 4.0 technologies and the conceptualization of new supply chain configurations for online retail, sustainable and green supply chains, and the Circular Economy. Thus, there is an increasing impetus to use simulation techniques such as discrete-event simulation, agent-based simulation, and hybrid simulation in the context of SCM. In conventional supply chain simulation, the underlying constituents of the system like manufacturing, distribution, retail, and logistics processes are often modelled and executed as a single model. Unlike this conventional approach, a distributed supply chain simulation (DSCS) enables the coordinated execution of simulation models using specialist software. To understand the current state-of-the-art of DSCS, this paper presents a methodological review and categorization of literature in DSCS using a framework-based approach. Through a study of over 130 articles, we report on the motivation for using DSCS, the modelling techniques, the underlying distributed computing technologies and middleware, its advantages and a future agenda, and also limitations and trade-offs that may be associated with this approach. The increasing adoption of technologies like Internet-of-Things and Cloud Computing will ensure the availability of both data and models for distributed decision-making, which is likely to enable data-driven DSCS of the future. This review aims to inform organizational stakeholders, simulation researchers and practitioners, distributed systems developers and software vendors, as to the current state-of-the art of DSCS, and which will inform the development of future DSCS using new applied computing approaches.

AN AGENT-BASED APPROACH FOR MODELING THE EFFECT OF LEARNING CURVE ON LABOR PRODUCTIVITY BRIDGES

2016 ◽  
Vol 3 (1) ◽  
Author(s):  
H. Shehwaro ◽  
E. Zankoul ◽  
H. Khoury
Keyword(s):  
Learning Curve ◽  
Labor Productivity ◽  
Construction Projects ◽  
Discrete Event ◽  
Cost Savings ◽  
Agent Based Modeling ◽  
Agent Based ◽  
Event Simulation ◽  
Adaptive Environment ◽  
Labor Resources

The labor-intensive nature of construction projects requires proper management and efficient utilization of labor resources. Improvement of labor productivity can enhance project performance and thereby lead to substantial time and cost savings. Several studies focused on identifying the effect of different factors on labor productivity, whereby the learning curve factor proved of paramount importance. Although previous research efforts developed models to represent the learning curve effect using traditional simulation approaches such as System Dynamics (SD) and Discrete Event Simulation (DES), none of these studies used Agent-Based Modeling (ABM) techniques. This study takes the initial steps and presents work targeted at analyzing the effect of learning on labor productivity using ABM. Based on ABM, a construction site can be modeled as an active environment in which agents interact with each other and their surroundings thereby creating an adaptive environment open for learning and improvement. The solution to the problem is described in details using a simulation model developed in AnyLogic 7 (Educational Version). The components of the proposed model have been created and preliminary results highlighted the potential of using the agent-based modeling paradigm to simulate the effect of learning on labor productivity in the construction industry

scholarly journals How Can Hybrid Simulation Support Organizations in Assessing COVID-19 Containment Measures?

Healthcare ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1412
Author(s):  
Chiara Cimini ◽  
Giuditta Pezzotta ◽  
Alexandra Lagorio ◽  
Fabiana Pirola ◽  
Sergio Cavalieri
Keyword(s):  
Discrete Event ◽  
Hybrid Simulation ◽  
Simulation Models ◽  
Indoor Environments ◽  
University Campus ◽  
Agent Based ◽  
Event Simulation ◽  
Support Organizations ◽  
Containment Measures

Simulation models have always been an aid in epidemiology for understanding the spread of epidemics and evaluating their containment policies. This paper illustrates how hybrid simulation can support companies in assessing COVID-19 containment measures in indoor environments. In particular, a Hybrid Simulation (HS) is presented. The HS model consists of an Agent-Based Simulation (ABS) to simulate the virus contagion model and a Discrete Event Simulation (DES) model to simulate the interactions between flows of people in an indoor environment. Compared with previous works in the field of simulation and COVID-19, this study provides the possibility to model the specific behaviors of individuals moving in time and space and the proposed HS model could be adapted to several epidemiological conditions (just setting different parameters in the agent-based model) and different kinds of facilities. The HS approach has been developed and then successfully tested with a real case study related to a university campus in northern Italy. The case study highlights the potentials of hybrid simulation in assessing the effectiveness of the containment measures adopted during the period under examination in the pandemic context. From a managerial perspective, this study, exploiting the complementarity of the ABM and DES approaches in a HS model, provides a complete and usable tool to support decision-makers in evaluating different contagion containment measures.

scholarly journals SAT modulo discrete event simulation applied to railway design capacity analysis

2021 ◽  
Author(s):  
Bjørnar Luteberget ◽  
Koen Claessen ◽  
Christian Johansen ◽  
Martin Steffen
Keyword(s):  
Discrete Event Simulation ◽  
Construction Projects ◽  
Software Verification ◽  
Ad Hoc ◽  
Discrete Event ◽  
Capacity Analysis ◽  
Railway Network ◽  
Event Simulation ◽  
Design Engineers ◽  
Railway Capacity

AbstractThis paper proposes a new method of combining SAT with discrete event simulation. This new integration proved useful for designing a solver for capacity analysis in early phase railway construction design. Railway capacity is complex to define and analyze, and existing tools and methods used in practice require comprehensive models of the railway network and its timetables. Design engineers working within the limited scope of construction projects report that only ad-hoc, experience-based methods of capacity analysis are available to them. Designs often have subtle capacity pitfalls which are discovered too late, only when network-wide timetables are made—there is a mismatch between the scope of construction projects and the scope of capacity analysis, as currently practiced. We suggest a language for capacity specifications suited for construction projects, expressing properties such as running time, train frequency, overtaking and crossing. Such specifications can be used as contracts in the interface between construction projects and network-wide capacity analysis. We show how these properties can be verified fully automatically by building a special-purpose solver which splits the problem into two: an abstracted SAT-based dispatch planning, and a continuous-domain dynamics with timing constraints evaluated using discrete event simulation. The two components communicate in a CEGAR loop (counterexample-guided abstraction refinement). This architecture is beneficial because it clearly distinguishes the combinatorial choices on the one hand from continuous calculations on the other, so that the simulation can be extended by relevant details as needed. We describe how loops in the infrastructure can be handled to eliminate repeating dispatch plans, and use case studies based on data from existing infrastructure and ongoing construction projects to show that our method is fast enough at relevant scales to provide agile verification in a design setting. Similar SAT modulo discrete event simulation combinations could also be useful elsewhere where one or both of these methods are already applicable such as in bioinformatics or hardware/software verification.

scholarly journals Simulation modeling and analysis of primary health center operations

SIMULATION ◽  
2021 ◽  
pp. 003754972110309
Author(s):  
Mohd Shoaib ◽  
Varun Ramamohan
Keyword(s):  
Resource Utilization ◽  
Waiting Times ◽  
Discrete Event ◽  
Simulation Models ◽  
Modeling And Analysis ◽  
Healthcare Facilities ◽  
Event Simulation ◽  
Analytical Approximations ◽  
Primary Health ◽  
Generic Modeling

We present discrete-event simulation models of the operations of primary health centers (PHCs) in the Indian context. Our PHC simulation models incorporate four types of patients seeking medical care: outpatients, inpatients, childbirth cases, and patients seeking antenatal care. A generic modeling approach was adopted to develop simulation models of PHC operations. This involved developing an archetype PHC simulation, which was then adapted to represent two other PHC configurations, differing in numbers of resources and types of services provided, encountered during PHC visits. A model representing a benchmark configuration conforming to government-mandated operational guidelines, with demand estimated from disease burden data and service times closer to international estimates (higher than observed), was also developed. Simulation outcomes for the three observed configurations indicate negligible patient waiting times and low resource utilization values at observed patient demand estimates. However, simulation outcomes for the benchmark configuration indicated significantly higher resource utilization. Simulation experiments to evaluate the effect of potential changes in operational patterns on reducing the utilization of stressed resources for the benchmark case were performed. Our analysis also motivated the development of simple analytical approximations of the average utilization of a server in a queueing system with characteristics similar to the PHC doctor/patient system. Our study represents the first step in an ongoing effort to establish the computational infrastructure required to analyze public health operations in India and can provide researchers in other settings with hierarchical health systems, a template for the development of simulation models of their primary healthcare facilities.

scholarly journals Assessing asset monitoring levels for maintenance operations

2015 ◽  
Vol 26 (5) ◽  
pp. 632-659 ◽  
Author(s):  
Abdullah A Alabdulkarim ◽  
Peter Ball ◽  
Ashutosh Tiwari
Keyword(s):  
Asset Management ◽  
Business Models ◽  
Discrete Event ◽  
Dynamic Modelling ◽  
Simulation Models ◽  
Content Type ◽  
Event Simulation ◽  
Product Service ◽  
Asset Monitoring ◽  
The Impact

Purpose – Asset management has recently gained significance due to emerging business models such as Product Service Systems where the sale of asset use, rather than the sale of the asset itself, is applied. This leaves the responsibility of the maintenance tasks to fall on the shoulders of the manufacturer/supplier to provide high asset availability. The use of asset monitoring assists in providing high availability but the level of monitoring and maintenance needs to be assessed for cost effectiveness. There is a lack of available tools and understanding of their value in assessing monitoring levels. The paper aims to discuss these issues. Design/methodology/approach – This research aims to develop a dynamic modelling approach using Discrete Event Simulation (DES) to assess such maintenance systems in order to provide a better understanding of the behaviour of complex maintenance operations. Interviews were conducted and literature was analysed to gather modelling requirements. Generic models were created, followed by simulation models, to examine how maintenance operation systems behave regarding different levels of asset monitoring. Findings – This research indicates that DES discerns varying levels of complexity of maintenance operations but that more sophisticated asset monitoring levels will not necessarily result in a higher asset performance. The paper shows that it is possible to assess the impact of monitoring levels as well as make other changes to system operation that may be more or less effective. Practical implications – The proposed tool supports the maintenance operations decision makers to select the appropriate asset monitoring level that suits their operational needs. Originality/value – A novel DES approach was developed to assess asset monitoring levels for maintenance operations. In applying this quantitative approach, it was demonstrated that higher asset monitoring levels do not necessarily result in higher asset availability. The work provides a means of evaluating the constraints in the system that an asset is part of rather than focusing on the asset in isolation.

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