Introducing multiobjective complex systems

•Theory of multiobjective complex systems.•Development of a graph based representation of complex systems.•Algorithmic solution approaches for multiobjective complex systems.•Compromise between subsystems. This article focuses on the optimization of a complex system which is composed of several subs...

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Vydáno v:European journal of operational research Ročník 280; číslo 2; s. 581 - 596
Hlavní autoři: Dietz, Tobias, Klamroth, Kathrin, Kraus, Konstantin, Ruzika, Stefan, Schäfer, Luca E., Schulze, Britta, Stiglmayr, Michael, Wiecek, Margaret M.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier B.V 16.01.2020
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ISSN:0377-2217, 1872-6860
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Abstract •Theory of multiobjective complex systems.•Development of a graph based representation of complex systems.•Algorithmic solution approaches for multiobjective complex systems.•Compromise between subsystems. This article focuses on the optimization of a complex system which is composed of several subsystems. On the one hand, these subsystems are subject to multiple objectives, local constraints as well as local variables, and they are associated with an own, subsystem-dependent decision maker. On the other hand, these subsystems are interconnected to each other by global variables or linking constraints. Due to these interdependencies, it is in general not possible to simply optimize each subsystem individually to improve the performance of the overall system. This article introduces a formal graph-based representation of such complex systems and generalizes the classical notions of feasibility and optimality to match this complex situation. Moreover, several algorithmic approaches are suggested and analyzed.
AbstractList •Theory of multiobjective complex systems.•Development of a graph based representation of complex systems.•Algorithmic solution approaches for multiobjective complex systems.•Compromise between subsystems. This article focuses on the optimization of a complex system which is composed of several subsystems. On the one hand, these subsystems are subject to multiple objectives, local constraints as well as local variables, and they are associated with an own, subsystem-dependent decision maker. On the other hand, these subsystems are interconnected to each other by global variables or linking constraints. Due to these interdependencies, it is in general not possible to simply optimize each subsystem individually to improve the performance of the overall system. This article introduces a formal graph-based representation of such complex systems and generalizes the classical notions of feasibility and optimality to match this complex situation. Moreover, several algorithmic approaches are suggested and analyzed.
Author Kraus, Konstantin
Klamroth, Kathrin
Schäfer, Luca E.
Schulze, Britta
Stiglmayr, Michael
Ruzika, Stefan
Dietz, Tobias
Wiecek, Margaret M.
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  givenname: Luca E.
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  surname: Stiglmayr
  fullname: Stiglmayr, Michael
  email: stiglmayr@math.uni-wuppertal.de
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  givenname: Margaret M.
  surname: Wiecek
  fullname: Wiecek, Margaret M.
  organization: Department of Mathematical Sciences, Clemson University, SC, USA
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Issue 2
Keywords Decomposition
Complex systems
Linking
Multiple objective programming
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SubjectTerms Complex systems
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Linking
Multiple objective programming
Title Introducing multiobjective complex systems
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