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Implementing hybrid simulations that integrate DES+SD in Python
Implementation of hybrid simulation is not well documented, and often obscured behind commercial software packages. Here two implementation approaches for integrating discrete event simulation and systems dynamics are presented in an open, reproducible framework, built with the Ciw library in Python...
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Published in: | Journal of simulation : JOS 2023-05, Vol.17 (3), p.240-256 |
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cites | cdi_FETCH-LOGICAL-c2722-cbfa5417894107a3a7b7ed419e89b7ebbbaf3c879f807f3cf64a507ff92e05693 |
container_end_page | 256 |
container_issue | 3 |
container_start_page | 240 |
container_title | Journal of simulation : JOS |
container_volume | 17 |
creator | Palmer, Geraint I. Tian, Yawen |
description | Implementation of hybrid simulation is not well documented, and often obscured behind commercial software packages. Here two implementation approaches for integrating discrete event simulation and systems dynamics are presented in an open, reproducible framework, built with the Ciw library in Python. These two implementation approaches, denoted here by
and
, correspond to two different process environments for DES+SD hybrid simulations. The models contribute to a collection of accessible and transparent hybrid simulations to be reproduced, scrutinised, built upon, and further developed. This paper also presents discussion on the lessons learned from these implementations, including the appropriateness of the models for different process environments, their ability to capture the full variability of a system, and subtleties in their synchronicity. |
doi_str_mv | 10.1080/17477778.2021.1992312 |
format | article |
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and
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and
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and
, correspond to two different process environments for DES+SD hybrid simulations. The models contribute to a collection of accessible and transparent hybrid simulations to be reproduced, scrutinised, built upon, and further developed. This paper also presents discussion on the lessons learned from these implementations, including the appropriateness of the models for different process environments, their ability to capture the full variability of a system, and subtleties in their synchronicity.</abstract><pub>Taylor & Francis</pub><doi>10.1080/17477778.2021.1992312</doi><tpages>17</tpages><oa>free_for_read</oa></addata></record> |
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subjects | discrete event simulation Hybrid simulation implementation open source systems dynamics |
title | Implementing hybrid simulations that integrate DES+SD in Python |
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