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Introduction Operations research, i.e. the application of scientific methodology to operational problems in the search for improved understanding and control, can be said to have started with the application of mathematical tools to military problems of supply bombing and strategy, during the Second World War. Post‐war these tools were applied to business problems, particularly production scheduling, inventory control and physical distribution because of the acute shortages of goods and the numerical aspects of these problems.

During recent years a number of techniques have been developed to aid in the forecasting of corporate sales, individual product demand, economic indicators, and other related series. These techniques have included classical time series analysis, multiple regression and adaptive forecasting procedures. As a result of these developments, the individual company and decision maker is faced with the task of selecting the forecasting technique that is most appropriate for his situation. This article reports research conducted at INSEAD on how simulation can be used to compare and evaluate alternative forecasting techniques for a specific application.

In recent times, the idea of taking advantage of the benefits of simulation techniques and Six Sigma discipline altogether has led various organizations towards implementation of simulation tools within Six Sigma methodology. The purpose of this study is to provide a more comprehensive literature review on the topic exploring how this amalgamation could work both in theory and practice. This precisely entailed finding dependable studies that shows how Six Sigma (DMAIC) Methodology can be enhanced by the three prevalent simulation techniques; Agent-Based (AB), Discrete-Events (DE), System Dynamics (SD).

A systematic literature review was considered more fitting in research because it involves rigorous and well-defined approach compared to other forms of literature review. In this case, the literature was comprehensive, well-encompassing and involved finding Six Sigma and Simulations literatures from reputable scholarly databases. The outcome of these reviews was the identification of a set of key finding compiled and classified by topics. The study follows an inductive approach and utilises a meta-synthesis review technique.

As numerous studies assert, simulation techniques including AB, DE and SD are applicable tools in almost every stage of DMAIC, especially the Analyse, Improve and Control phases, because of their capability to test and identify potential bottlenecks and improvement areas. Findings show that the simulation tools such as CLDs, Group Model Building, Dynamic Balance Scorecards and Cost of poor quality all have the potential to add value to a Six Sigma methodology.

The findings of this study highlight the importance of further inquiry in this area of study. The finding of this study suggests that although the study on the integration of Six Sigma and simulations is increasing, empirical evidence on its effectiveness is still limited. Therefore, this study suggests more roadmaps and investigations aimed at merging Six Sigma methodology and various simulation technique. Moreover, studies that centre on hybrid or multi-method simulations within Six Sigma are also urgently necessitated.

Simulation is a well-known technique for using computers to imitate or simulate the operations of various kinds of real-world facilities or processes. The facility or process of interest is usually called a system, and to study it scientifically, we often have to make a set of assumptions about how it works. These assumptions, which usually take the form of mathematical or logical relationships, constitute a model that is used to gain some understanding of how the corresponding system behaves, and the quality of these understandings essentially depends on the credibility of given assumptions or models, known as VV&A (verification, validation and accreditation). The main purpose of this paper is to present an in-depth theoretical review and analysis for the application of VV&A in large-scale simulations.

After summarizing the VV&A of related research studies, the standards, frameworks, techniques, methods and tools have been discussed according to the characteristics of large-scale simulations (such as crowd network simulations).

The contributions of this paper will be useful for both academics and practitioners for formulating VV&A in large-scale simulations (such as crowd network simulations).

This paper will help researchers to provide support of a recommendation for formulating VV&A in large-scale simulations (such as crowd network simulations).

Hybrid simulation, which is a general technique for obtaining the seismic response of an entire structure, is an improvement of the traditional seismic test technique. In order to improve the analysis accuracy of the numerical substructure in hybrid simulation, the purpose of this paper is to propose an innovative hybrid simulation technique. The technique combines the multi-scale finite element (MFE) analysis method and hybrid simulation method with the objective of achieving the balance between the accuracy and efficiency for the numerical substructure simulation.

To achieve this goal, a hybrid simulation system is established based on the MTS servo control system to develop a hybrid analysis model using an MFE model. Moreover, in order to verify the efficiency of the technique, the hybrid simulation of a three-storey benchmark structure is conducted. In this simulation, a ductile column—represented by a half-scale scale specimen—is selected as the experimental element, meanwhile the rest of the frame is modelled as microscopic and macroscopic elements in the Abaqus software simultaneously. Finally, to demonstrate the stability and accuracy of the proposed technique, the seismic response of the target structure obtained via hybrid simulation using the MFE model is compared with that of the numerical simulation.

First, the use of the hybrid simulation with the MFE model yields results similar to those obtained by the fine finite element (FE) model using solid elements without adding excessive computing burden, thus advancing the application of the hybrid simulation in large complex structures. Moreover, the proposed hybrid simulation is found to be more versatile in structural seismic analysis than other techniques. Second, the hybrid simulation system developed in this paper can perform hybrid simulation with the MFE model as well as handle the integration and coupling of the experimental elements with the numerical substructure, which consists of the macro- and micro-level elements. Third, conducting the hybrid simulation by applying earthquake motion to simulate seismic structural behaviour is feasible by using Abaqus to model the numerical substructure and harmonise the boundary connections between three different scale elements.

In terms of the implementation of the hybrid simulation with the MFE model, this work is helpful to advance the hybrid simulation method in the structural experiment field. Nevertheless, there is still a need to refine and enhance the current technique, especially when the hybrid simulation is used in real complex engineering structures, having numerous micro-level elements. A large number of these elements may render the relevant hybrid simulations unattainable because the time consumed in the numeral calculations can become excessive, making the testing of the loading system almost difficult to run smoothly.

The MFE model is implemented in hybrid simulation, enabling to overcome the problems related to the testing accuracy caused by the numerical substructure simplifications using only macro-level elements.

This paper is the first to recognise the advantage of the MFE analysis method in hybrid simulation and propose an innovative hybrid simulation technique, combining the MFE analysis method with hybrid simulation method to strike a delicate balance between the accuracy and efficiency of the numerical substructure simulation in hybrid simulation. With the help of the coordinated analysis of FEs at different scales, not only the accuracy and reliability of the overall seismic analysis of the structure is improved, but the computational cost can be restrained to ensure the efficiency of hybrid simulation.

Simulation has attracted increasing attention in lean production research as a response to address the complexities of the production environment and difficulties of dealing with changes within a system. Considerable growth of using simulation to facilitate lean acceptance and implementation has been observed across different projects and sectors. However, a thorough review of the development and use of simulation in lean production research is limited.

This study aims to address this gap by reviewing 311 journal papers published in the past two decades on this specific research area and identify the state-of-the-art development and propose future research directions.

The review shows that current studies related to simulation in lean production research can be categorised into two major research streams, namely, simulation assisted lean facilitation and evaluation, and simulation-based lean education and training. Under the first research stream, a total of 19 application areas have been identified which applied both lean and simulation in their studies. The evolution of the simulation techniques used in these studies has been analysed as well. Meanwhile, four types of simulation games have been identified in the stream of simulation-based lean education and training and the impact and applicability of the different simulation and games have been discussed. A framework for engaging lean and simulation is suggested based on the review of the existing studies. The analysis in both streams also highlights the importance of stakeholder engagement and the utilisation of information technologies for future studies.

The findings of this study are expected to provide useful references for the future development and application of simulation in lean production research.

This paper conducted a broad and extensive review of simulation integrated lean production research. An in-depth examination of the retrieved papers was conducted through a structured and quantitative analysis to understand the current body of knowledge.

Project scheduling/rescheduling occurs in all stages of projects, from feasibility stage to monitoring stage to completion. Since the late 1950s, network‐based techniques CPM (critical path method) and PERT (programme evaluation review technique) are the techniques commonly used for project management. However, there are limitations in working with these tools that need to be overcome. Also, the computing ef. ciency of classic CPM/PERT analysis needs to be enhanced. Substantial research has been carried out globally in this field covering all areas of project scheduling: time scheduling, resource scheduling, cost scheduling, modern project management techniques, advanced mathematical models used for construction scheduling, and so on. To understand and document this research status, the authors have carried out an extensive study of various journals, published and unpublished research papers, and present this literature review.

Discusses computer modelling and simulation as a decision‐making technique frequently used by all genres of manager in a wide range of disciplines and in all types of organizations. Suggests that for auditors to do an effective job – a competent, quality audit in a timely and efficient way – they must familiarize themselves with the technique, know how it is used in the decision process and be aware of its shortcomings. Explores the many ways computer modelling and simulation are used in the decision process and discusses how the technique was actually used to facilitate several audits. Describes the use of computer modelling and simulation during an audit to validate an auditee‐developed model, simulate the outcome of an auditee′s plans, test an auditee′s in‐place system and, finally, help enhance the credibility of auditor recommendations.

The aim of this study is to identify the nodes where congestion occurs in the manoeuvring area of a large-scale airport and to provide appropriate suggestions for improvement.

To investigate the air traffic flow in a highly complex system such as an airport manoeuvring area, a two-stage method based on fast- and real-time simulation techniques is applied. The first stage involves the analysis with fast- and real-time simulations of a baseline model created to determine the congestion points. Based on the analysis, improvements to be performed in the layout of the manoeuvring area are proposed. In the second stage, alternative scenarios implementing these improvements are generated and evaluated in a fast-time simulation environment. Based on the results of simulations of different runway configurations, the main areas of congestion in the baseline airport model are determined. Congestion nodes are identified in the departure queue points and in the taxiway system. To mitigate congestion at these points, three alternative models comprising taxiway and fast-exit taxiway reconfigurations are tested using the fast-time simulation technique. The alternative solution found to be the best in these tests is selected for further testing in real-time simulations.

It is shown that the solution would result in an increase in the number of hourly operations and a significant decrease in total ground delays. When conducting the studies needed to identify congestion and design improvements, simulation techniques save both expense and time. Although fast-time simulations are usually adequate for identifying solutions, when critical configurations for the airport are considered, it is shown that it is necessary to also test the results of the fast-time simulations in real-time simulations.

The effects of meteorological events, such as rain, fog and snow, etc. are ignored in the simulations. Ground movements in manoeuvring areas are significantly affected by the runways used. Consequently, to enable a comprehensive evaluation in the study, three alternative runway use scenarios are examined.

This study utilizes a combination of fast- and real-time simulation techniques to identify the points where congestion occurs in the manoeuvring areas of large-scale airports and to find solutions to minimize the congestion. This approach attempts to combine advantages of both techniques while reducing their shortcomings. No study is found in the literature using both of these techniques together for the capacity analysis of airport manoeuvring areas.

Suggests that many quantitative methods have been developed in an attempt to acknowledge uncertainty in decision making and to manage the inherent risk during economic planning for new technology implementation. Outlines a relatively simple and practical risk analysis, accompanied by the implementation of advanced manufacturing technology. Employs the proven analytical hierarchy process (AHP) approach, coupled with confidence intervals from data gathered through simulation techniques or through observations and empirical sampling. Describes a case study in which simulation models were developed using a software package SIMFACTORY II.5, which is based on the concept of visual interactive simulation. A number of simulation experiments were performed in order to investigate the influence of various flexible manufacturing system and cellular manufacturing system configurations. An AHP multi‐attribute analysis is performed by using AUTOMAN, a decision support software package. This package evaluates and combines the qualitative and quantitative factors for different configuration designs.