Architectural Models Enabled Dynamic Optimization for System-of-Systems Evolution

System of Systems (SoS) is designed to deliver value to participant stakeholders in a dynamic and uncertain environment where new systems are added and current systems are removed continuously and on their own volition. This requires effective evolution management at the SoS architectural level with...

Full description

Bibliographic Details
Main Authors: Zhemei Fang, Xiaozhou Zhou, Ani Song
Format: Article
Language:English
Published: Hindawi-Wiley 2020-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2020/7534819
id doaj-281ee9a9f52d41cdae4471e56f642971
record_format Article
spelling doaj-281ee9a9f52d41cdae4471e56f6429712020-11-25T03:01:00ZengHindawi-WileyComplexity1076-27871099-05262020-01-01202010.1155/2020/75348197534819Architectural Models Enabled Dynamic Optimization for System-of-Systems EvolutionZhemei Fang0Xiaozhou Zhou1Ani Song2School of Artificial Intelligence and Automation, National Key Laboratory of Science and Technology on Multispectral Information Processing, Huazhong University of Science and Technology, Wuhan 430074, ChinaSchool of Artificial Intelligence and Automation, National Key Laboratory of Science and Technology on Multispectral Information Processing, Huazhong University of Science and Technology, Wuhan 430074, ChinaSchool of Electrical and Electronic Engineering, Hubei University of Technology, Wuhan 430068, ChinaSystem of Systems (SoS) is designed to deliver value to participant stakeholders in a dynamic and uncertain environment where new systems are added and current systems are removed continuously and on their own volition. This requires effective evolution management at the SoS architectural level with adequate support of process, methods, and tools. This paper follows the principle of Model-Based Systems Engineering (MBSE) and develops a holistic framework integrating MBSE conceptual representations and approximate dynamic programming (ADP) to support the SoS evolution. The conceptual models provide a common architectural representation to improve communication between various decision makers while the dynamic optimization method suggests evolution planning decisions from the analytical perspective. The Department of Defense Architecture Framework (DoDAF) models using Systems Modeling Language (SysML) are used as MBSE artifacts to connect with ADP modeling elements through DoDAF metamodels to increase information traceability and reduce unnecessary information loss. Using a surface warfare SoS as an example, this paper demonstrates and explains the procedures of developing DoDAF models, mapping DoDAF models to ADP elements, formulating ADP formulation, and generating evolutionary decisions. The effectiveness of using ADP in supporting evolution to achieve a near-optimal solution that can maximize the SoS capability over time is illustrated by comparing ADP solution to other alternative solutions. The entire framework also sheds light on bridging the DoDAF-based conceptual models and other mathematical optimization methods.http://dx.doi.org/10.1155/2020/7534819
collection DOAJ
language English
format Article
sources DOAJ
author Zhemei Fang
Xiaozhou Zhou
Ani Song
spellingShingle Zhemei Fang
Xiaozhou Zhou
Ani Song
Architectural Models Enabled Dynamic Optimization for System-of-Systems Evolution
Complexity
author_facet Zhemei Fang
Xiaozhou Zhou
Ani Song
author_sort Zhemei Fang
title Architectural Models Enabled Dynamic Optimization for System-of-Systems Evolution
title_short Architectural Models Enabled Dynamic Optimization for System-of-Systems Evolution
title_full Architectural Models Enabled Dynamic Optimization for System-of-Systems Evolution
title_fullStr Architectural Models Enabled Dynamic Optimization for System-of-Systems Evolution
title_full_unstemmed Architectural Models Enabled Dynamic Optimization for System-of-Systems Evolution
title_sort architectural models enabled dynamic optimization for system-of-systems evolution
publisher Hindawi-Wiley
series Complexity
issn 1076-2787
1099-0526
publishDate 2020-01-01
description System of Systems (SoS) is designed to deliver value to participant stakeholders in a dynamic and uncertain environment where new systems are added and current systems are removed continuously and on their own volition. This requires effective evolution management at the SoS architectural level with adequate support of process, methods, and tools. This paper follows the principle of Model-Based Systems Engineering (MBSE) and develops a holistic framework integrating MBSE conceptual representations and approximate dynamic programming (ADP) to support the SoS evolution. The conceptual models provide a common architectural representation to improve communication between various decision makers while the dynamic optimization method suggests evolution planning decisions from the analytical perspective. The Department of Defense Architecture Framework (DoDAF) models using Systems Modeling Language (SysML) are used as MBSE artifacts to connect with ADP modeling elements through DoDAF metamodels to increase information traceability and reduce unnecessary information loss. Using a surface warfare SoS as an example, this paper demonstrates and explains the procedures of developing DoDAF models, mapping DoDAF models to ADP elements, formulating ADP formulation, and generating evolutionary decisions. The effectiveness of using ADP in supporting evolution to achieve a near-optimal solution that can maximize the SoS capability over time is illustrated by comparing ADP solution to other alternative solutions. The entire framework also sheds light on bridging the DoDAF-based conceptual models and other mathematical optimization methods.
url http://dx.doi.org/10.1155/2020/7534819
work_keys_str_mv AT zhemeifang architecturalmodelsenableddynamicoptimizationforsystemofsystemsevolution
AT xiaozhouzhou architecturalmodelsenableddynamicoptimizationforsystemofsystemsevolution
AT anisong architecturalmodelsenableddynamicoptimizationforsystemofsystemsevolution
_version_ 1715327561750282240