Pub Date : 2023-01-16DOI: 10.1080/17477778.2022.2163933
Kisun Bae, H. Ko
{"title":"Installation planning for an offshore wind farm: a hybrid modelling framework of integrating simulation and optimisation with a Markov Chain","authors":"Kisun Bae, H. Ko","doi":"10.1080/17477778.2022.2163933","DOIUrl":"https://doi.org/10.1080/17477778.2022.2163933","url":null,"abstract":"","PeriodicalId":51296,"journal":{"name":"Journal of Simulation","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2023-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48889690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-08DOI: 10.1080/17477778.2023.2165460
S. Elsawah, H. Turan, Lindsay Gordon, M. Ryan
{"title":"A decision support methodology to support military asset and resource planning","authors":"S. Elsawah, H. Turan, Lindsay Gordon, M. Ryan","doi":"10.1080/17477778.2023.2165460","DOIUrl":"https://doi.org/10.1080/17477778.2023.2165460","url":null,"abstract":"","PeriodicalId":51296,"journal":{"name":"Journal of Simulation","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2023-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44770682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-03DOI: 10.1080/17477778.2022.2152394
M. Conlon, O. Molloy
ABSTRACT Demand for computed tomography (CT) and CT waiting lists are growing, a problem exacerbated by the postponement of scheduled services during the Covid-19 pandemic. In this case study operational research (OR) methods were used to investigate resource utilisation and CT waiting list growth. Stakeholder involvement was facilitated using system dynamics (SD) for problem conceptualisation and Soft Systems Methodology (SSM) to identify service issues, data requirements, and scenarios for testing. Discrete event simulation (DES) was used to generate metrics pertaining to daily staff work load, process performance (delays) and waiting list evolution, for the current and alternative scenarios. Lessons learnt from the perspective of a clinical modeller are discussed throughout. DES model outputs illustrated the high daily variation in resource utilisation and process delays for the current service where inpatients and outpatients share a single CT scanner. Inpatient examinations were found to consume on average 23% more staff time than outpatient. For non-contrast CT scans, outpatients consumed 63% less time than inpatients. Simulation results for an outpatient-only service demonstrated higher CT and healthcare assistant utilisation, with low variation and process delays. This work recommends the separation of inpatient and outpatient CT services to address the problem of growing CT waiting lists.
{"title":"Modelling a Computed Tomography service using mixed Operational Research methods","authors":"M. Conlon, O. Molloy","doi":"10.1080/17477778.2022.2152394","DOIUrl":"https://doi.org/10.1080/17477778.2022.2152394","url":null,"abstract":"ABSTRACT Demand for computed tomography (CT) and CT waiting lists are growing, a problem exacerbated by the postponement of scheduled services during the Covid-19 pandemic. In this case study operational research (OR) methods were used to investigate resource utilisation and CT waiting list growth. Stakeholder involvement was facilitated using system dynamics (SD) for problem conceptualisation and Soft Systems Methodology (SSM) to identify service issues, data requirements, and scenarios for testing. Discrete event simulation (DES) was used to generate metrics pertaining to daily staff work load, process performance (delays) and waiting list evolution, for the current and alternative scenarios. Lessons learnt from the perspective of a clinical modeller are discussed throughout. DES model outputs illustrated the high daily variation in resource utilisation and process delays for the current service where inpatients and outpatients share a single CT scanner. Inpatient examinations were found to consume on average 23% more staff time than outpatient. For non-contrast CT scans, outpatients consumed 63% less time than inpatients. Simulation results for an outpatient-only service demonstrated higher CT and healthcare assistant utilisation, with low variation and process delays. This work recommends the separation of inpatient and outpatient CT services to address the problem of growing CT waiting lists.","PeriodicalId":51296,"journal":{"name":"Journal of Simulation","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2023-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41714366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-15DOI: 10.1080/17477778.2022.2152395
Aydin Teymourifar
{"title":"Simulation-based optimization for resectorization in healthcare systems","authors":"Aydin Teymourifar","doi":"10.1080/17477778.2022.2152395","DOIUrl":"https://doi.org/10.1080/17477778.2022.2152395","url":null,"abstract":"","PeriodicalId":51296,"journal":{"name":"Journal of Simulation","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47055321","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-15DOI: 10.1080/17477778.2022.2155258
Nicholas D. Bernardo, Bridgett A. King, Gretchen A. Macht
{"title":"COVID-19 and United States Election systems: a simulation study of in-person voting in Rhode Island","authors":"Nicholas D. Bernardo, Bridgett A. King, Gretchen A. Macht","doi":"10.1080/17477778.2022.2155258","DOIUrl":"https://doi.org/10.1080/17477778.2022.2155258","url":null,"abstract":"","PeriodicalId":51296,"journal":{"name":"Journal of Simulation","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42443294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-05DOI: 10.1080/17477778.2022.2150578
P. Bhanu, T. V. Krishna Mohan, R. Amit, Venugopal Shankar
{"title":"Factors affecting the market dynamics of lithium-ion battery for electric mobility: a system dynamics perspective","authors":"P. Bhanu, T. V. Krishna Mohan, R. Amit, Venugopal Shankar","doi":"10.1080/17477778.2022.2150578","DOIUrl":"https://doi.org/10.1080/17477778.2022.2150578","url":null,"abstract":"","PeriodicalId":51296,"journal":{"name":"Journal of Simulation","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2022-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47571684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-04DOI: 10.1080/17477778.2022.2147034
A. S. White, L. Brodie, M. Censlive
ABSTRACT The research investigated whether Perceptual Control Theory (PCT) can be used to model the decisions of small groups utilizing data from the Beer Game. The PCT model was tested on public and MSc data operating the Beer Game. Investigations of closed-loop behaviour determined the perceived disturbance was the controlled variable. A set of PCT Simulink models was built and their parameters adjusted to give responses comparable to the human Beer Game based on the groups’ orders alone. A few groups appear to have additionally used the backlog as input. PCT, incorporating the principle of closed loop control, does represent the human management of the Beer Game, giving an overall correlation coefficient of 0.70-0.74 obtained between the orders from a PCT model and those used in the Beer Game from 14 groups of participants and supported by minimum weighted integrals IAE and ITAE and Kolmogorov-Smirnov 2 sample tests.
{"title":"Application of perceptual control theory to a Beer Game supply chain model","authors":"A. S. White, L. Brodie, M. Censlive","doi":"10.1080/17477778.2022.2147034","DOIUrl":"https://doi.org/10.1080/17477778.2022.2147034","url":null,"abstract":"ABSTRACT The research investigated whether Perceptual Control Theory (PCT) can be used to model the decisions of small groups utilizing data from the Beer Game. The PCT model was tested on public and MSc data operating the Beer Game. Investigations of closed-loop behaviour determined the perceived disturbance was the controlled variable. A set of PCT Simulink models was built and their parameters adjusted to give responses comparable to the human Beer Game based on the groups’ orders alone. A few groups appear to have additionally used the backlog as input. PCT, incorporating the principle of closed loop control, does represent the human management of the Beer Game, giving an overall correlation coefficient of 0.70-0.74 obtained between the orders from a PCT model and those used in the Beer Game from 14 groups of participants and supported by minimum weighted integrals IAE and ITAE and Kolmogorov-Smirnov 2 sample tests.","PeriodicalId":51296,"journal":{"name":"Journal of Simulation","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2022-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43301394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-18DOI: 10.1080/17477778.2022.2145243
Verônica Ghisolfi, L. Tavasszy, Gonçalo Homem de Almeida Rodriguez Correia, Gisele de Lorena Diniz Chaves, G. Ribeiro
{"title":"Dynamics of freight transport decarbonisation: a conceptual model","authors":"Verônica Ghisolfi, L. Tavasszy, Gonçalo Homem de Almeida Rodriguez Correia, Gisele de Lorena Diniz Chaves, G. Ribeiro","doi":"10.1080/17477778.2022.2145243","DOIUrl":"https://doi.org/10.1080/17477778.2022.2145243","url":null,"abstract":"","PeriodicalId":51296,"journal":{"name":"Journal of Simulation","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2022-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44729152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-02DOI: 10.1080/17477778.2022.2080009
A. Falcone, A. Garro, N. Mustafee, M. Niazi, Gabriel A. Wainer
Modelling and Simulation (M&S) represents one of the fundamental methods to design and study complex systems in many industrial and scientific domains such as transport, energy, and aerospace. M&S techniques enable the analysis and evaluation of many design alternatives while avoiding risks, costs, and failures that come with experimentations on the real system; this opportunity becomes crucial, when realworld tests are too costly to conduct in terms of safety, time, and other resources (Fujimoto et al., 2017). Cloud Computing has captured the interest of the scientific and industrial communities because of the benefits provided by its service models, i.e., Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). These services allow developers to rapidly implement solutions that exploit computing and data storage capacity, network resources, and scalability, without having to deal with common issues related to the configuration of the Cloud infrastructure that is automatically managed by a specific service. Cloud Computing can be defined as a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., servers, storage, and services) that can be rapidly provisioned and released with minimal effort in management (Mell & Grance, 2011). In this context, Cloud, Fog, and Edge computing allow organisations to exploit data processing and storage resources efficiently through the definition of a hierarchical data processing architecture. Fog and Edge computing are both extensions of the Cloud network, where at the lowest level there is the Edge, followed by the Fog level, and finally the Cloud level. The Edge layer allows reducing network traffic as data processing occurs locally on the devices. The Fog layer of the Cloud network architecture pushes intelligence down to the LAN layer, where data are processed in a gateway; thus, the Fog nodes are placed near devices with which it is communicating. Cloud, Fog, and Edge computing can offer suitable services to share and collaborate on M&S projects and perform complex simulation experiments faster and more efficiently through the Modelling and Simulation as a Service (MSaaS) model. While MSaaS provides an everincreasing number of opportunities, it also poses a significant number of pitfalls. One of the major pitfalls is that Cloud infrastructures are massive at all scales; as a consequence, the definition of MSaaS solutions is difficult without a deep knowledge of the involved infrastructures and technologies (Cayirci, 2013). The focus of this special issue is to provide current research results in M&S for Cloud Computing and vice versa. Specifically, the special issue aims at (i) presenting the current state-of-the-art about M&S solutions based on open standards, recent extensions, and innovations related to Cloud Computing technologies; (ii) identifying research directions and technologies that w
{"title":"Editorial: Special issue on modelling and simulation in the cloud computing era","authors":"A. Falcone, A. Garro, N. Mustafee, M. Niazi, Gabriel A. Wainer","doi":"10.1080/17477778.2022.2080009","DOIUrl":"https://doi.org/10.1080/17477778.2022.2080009","url":null,"abstract":"Modelling and Simulation (M&S) represents one of the fundamental methods to design and study complex systems in many industrial and scientific domains such as transport, energy, and aerospace. M&S techniques enable the analysis and evaluation of many design alternatives while avoiding risks, costs, and failures that come with experimentations on the real system; this opportunity becomes crucial, when realworld tests are too costly to conduct in terms of safety, time, and other resources (Fujimoto et al., 2017). Cloud Computing has captured the interest of the scientific and industrial communities because of the benefits provided by its service models, i.e., Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). These services allow developers to rapidly implement solutions that exploit computing and data storage capacity, network resources, and scalability, without having to deal with common issues related to the configuration of the Cloud infrastructure that is automatically managed by a specific service. Cloud Computing can be defined as a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., servers, storage, and services) that can be rapidly provisioned and released with minimal effort in management (Mell & Grance, 2011). In this context, Cloud, Fog, and Edge computing allow organisations to exploit data processing and storage resources efficiently through the definition of a hierarchical data processing architecture. Fog and Edge computing are both extensions of the Cloud network, where at the lowest level there is the Edge, followed by the Fog level, and finally the Cloud level. The Edge layer allows reducing network traffic as data processing occurs locally on the devices. The Fog layer of the Cloud network architecture pushes intelligence down to the LAN layer, where data are processed in a gateway; thus, the Fog nodes are placed near devices with which it is communicating. Cloud, Fog, and Edge computing can offer suitable services to share and collaborate on M&S projects and perform complex simulation experiments faster and more efficiently through the Modelling and Simulation as a Service (MSaaS) model. While MSaaS provides an everincreasing number of opportunities, it also poses a significant number of pitfalls. One of the major pitfalls is that Cloud infrastructures are massive at all scales; as a consequence, the definition of MSaaS solutions is difficult without a deep knowledge of the involved infrastructures and technologies (Cayirci, 2013). The focus of this special issue is to provide current research results in M&S for Cloud Computing and vice versa. Specifically, the special issue aims at (i) presenting the current state-of-the-art about M&S solutions based on open standards, recent extensions, and innovations related to Cloud Computing technologies; (ii) identifying research directions and technologies that w","PeriodicalId":51296,"journal":{"name":"Journal of Simulation","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2022-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42740498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-12DOI: 10.1080/17477778.2022.2128911
Cristina Duran Casablancas, M. Holtman, M. Strlič, J. Grau-Bové
Digitisation has become an essential part of archival and library strategies to enhance access to collections. As the digital content is increasing due to large-scale digitisation projects, it is expected that providing digital access to the analogue collections will eventually reduce the number of archival records accessed in the reading room. In this paper, we investigate this issue using two approaches: system dynamics and agent-based modelling. We first analyse real data in order to identify the dynamic hypothesis of the model. Then, a sensitivity analysis is conducted on two baseline models to identify scenarios that match the real dataset. Although the two approaches suceed to simulate the number of requests in the reading room, the experimental results show that a better fit is obtained in the agent-based model when not only the number of records that have been accessed and digitised is taken into account, but also the number of times that such records have been accessed before digitisation. The proposed model can be used to explore the impact of different digitisation strategies on the decrease in access requests in the archival and library reading rooms.
{"title":"The end of the reading room? Simulating the impact of digitisation on the physical access of archival collections","authors":"Cristina Duran Casablancas, M. Holtman, M. Strlič, J. Grau-Bové","doi":"10.1080/17477778.2022.2128911","DOIUrl":"https://doi.org/10.1080/17477778.2022.2128911","url":null,"abstract":"Digitisation has become an essential part of archival and library strategies to enhance access to collections. As the digital content is increasing due to large-scale digitisation projects, it is expected that providing digital access to the analogue collections will eventually reduce the number of archival records accessed in the reading room. In this paper, we investigate this issue using two approaches: system dynamics and agent-based modelling. We first analyse real data in order to identify the dynamic hypothesis of the model. Then, a sensitivity analysis is conducted on two baseline models to identify scenarios that match the real dataset. Although the two approaches suceed to simulate the number of requests in the reading room, the experimental results show that a better fit is obtained in the agent-based model when not only the number of records that have been accessed and digitised is taken into account, but also the number of times that such records have been accessed before digitisation. The proposed model can be used to explore the impact of different digitisation strategies on the decrease in access requests in the archival and library reading rooms.","PeriodicalId":51296,"journal":{"name":"Journal of Simulation","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2022-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47750277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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