Framework for Multi-Level Optimization of Complex Systems

2010 ◽  
pp. 347-377
Author(s):  
Albert de Wit ◽  
Fred van Keulen
Keyword(s):  
Complex Systems ◽  
Multi Level

Multi-level, partitioned response surfaces for modeling complex systems

1998 ◽  
Author(s):  
Patrick Koch ◽  
Dimitri Mavris ◽  
Farrokh Mistree
Keyword(s):  
Complex Systems ◽  
Response Surfaces ◽  
Multi Level

Catalogue Design of Technical Systems Based on a Resource Exchange Paradigm

1996 ◽  
Author(s):  
Michael Heinrich ◽  
Werner E. Juengst
Keyword(s):  
Complex Systems ◽  
Mechanical Systems ◽  
Resource Exchange ◽  
Short Introduction ◽  
Multi Level ◽  
Technical Systems

Abstract In this paper, we illustrate the use of the resource exchange paradigm for mechanical systems and, through multi-level configuration, for complex systems. To make this paper self-contained, a short introduction to resource-based modelling is included.

Complex systems models for causal inference in social epidemiology

2020 ◽  
Vol 75 (7) ◽  
pp. 702-708
Author(s):  
Hiba N Kouser ◽  
Ruby Barnard-Mayers ◽  
Eleanor Murray
Keyword(s):  
Complex Systems ◽  
Causal Inference ◽  
Social Inequalities ◽  
Social Epidemiology ◽  
Causal Effects ◽  
Natural Choice ◽  
Systems Models ◽  
Multi Level

Systems models, which by design aim to capture multi-level complexity, are a natural choice of tool for bridging the divide between social epidemiology and causal inference. In this commentary, we discuss the potential uses of complex systems models for improving our understanding of quantitative causal effects in social epidemiology. To put systems models in context, we will describe how this approach could be used to optimise the distribution of COVID-19 response resources to minimise social inequalities during and after the pandemic.

scholarly journals From inert matter to the global society life as multi-level networks of processes

2020 ◽  
Vol 375 (1796) ◽  
pp. 20190329 ◽  
Author(s):  
David Chavalarias
Keyword(s):  
Complex Systems ◽  
Biological Networks ◽  
Theoretical Biology ◽  
Life Forms ◽  
New Paradigm ◽  
Philosophical Foundations ◽  
Process Networks ◽  
The Face ◽  
Multi Level ◽  
To Come

A few billion years have passed since the first life forms appeared. Since then, life has continued to forge complex associations between the different emergent levels of interconnection it forms. The advances of recent decades in molecular chemistry and theoretical biology, which have embraced complex systems approaches, now make it possible to conceptualize the questions of the origins of life and its increasing complexity from three complementary notions of closure: processes closure, autocatalytic closure and constraints closure. Developed in the wake of the second-order cybernetics, this triple closure approach, that relies on graph theory and complex networks science, sketch a paradigm where it is possible to go up the physical levels of organization of matter, from physics to biology and society, without resorting to strong reductionism. The phenomenon of life is conceived as the contingent complexification of the organization of matter, until the emergence of life forms, defined as a network of auto-catalytic process networks, organized in a multi-level manner. This approach of living systems, initiated by Maturana & Varela and Kauffman, inevitably leads to a reflection on the nature of cognition; and in the face of the deep changes that affected humanity as a complex systems, on the nature of cultural evolution. Faced with the major challenges that humanity will have to address in the decades to come, this new paradigm invites us to change our conception of causality by shifting our attention from state change to process change and to abandon a widespread notion of 'local' causality in favour of complex systems thinking. It also highlights the importance of a better understanding of the influence of social networks, recommendation systems and artificial intelligence on our future collective dynamics and social cognition processes. This article is part of the theme issue ‘Unifying the essential concepts of biological networks: biological insights and philosophical foundations’.

Multi-level approach for important component identification and reliability evaluation for complex system by survival signature

2019 ◽  
Vol 37 (1) ◽  
pp. 262-288
Author(s):  
Liling Ge ◽  
Yingjie Zhang
Keyword(s):  
Complex System ◽  
Complex Systems ◽  
Reliability Analysis ◽  
Production System ◽  
Content Type ◽  
Actual Production ◽  
Machining System ◽  
Multi Level ◽  
Critical Components

Purpose The purpose of this paper is to identify the critical components of a complex system by using survival signature. First, a complex system is abstracted with varying scales and generates a multi-levels model. Then reliability evaluations can be conducted by survival signature from rough to fine for tracing and identifying them. Finally, the feasibility of the proposed approach is demonstrated by an actual production system. Design/methodology/approach The paper mainly applies a multi-level evaluating strategy for the reliability analysis of complex systems with components of multiple types. In addition, a multi-levels model of a complex system is constructed and survival signature also used for evaluation. Findings The proposed approach was demonstrated to be the feasibility by an actual production system that is used in the case study. Research limitations/implications The case study was performed on a system with simple network structure, but the proposed approach could be applied to systems with complex ones. However, the approach to generate the digraphs of abstraction levels for complex system has to be developed. Practical implications So far the approach has been used for the reliability analysis of a machining system. The approach that is proposed for the identification of critical components also can be applied to make maintenance decision. Originality/value The multi-level evaluating strategy that was proposed for reliability analysis and the identification of critical components of complex systems was a novel method, and it also can be applied as index to make maintenance planning.

scholarly journals Exploring, browsing and interacting with multi-level and multi-scale dynamics of knowledge

2021 ◽  
pp. 147387162110448
Author(s):  
Quentin Lobbé ◽  
Alexandre Delanoë ◽  
David Chavalarias
Keyword(s):  
Complex Systems ◽  
State Of The Art ◽  
Free Software ◽  
Discovery Process ◽  
Multi Scale ◽  
Computational Sciences ◽  
Knowledge Dynamics ◽  
Multi Level ◽  
Scale Properties ◽  
Ict Revolution

The ICT revolution has given birth to a world of digital traces. A wide number of knowledge-driven domains like science are daily fueled by unlimited flows of textual contents. In order to navigate across these growing constellations of words, interdisciplinary innovations are emerging at the crossroad between social and computational sciences. In particular, complex systems approaches make it now possible to reconstruct multi-level and multi-scale dynamics of knowledge by means of inheritance networks of elements of knowledge called phylomemies. In this article, we will introduce an endogenous way to visualize the multi-level and multi-scale properties of phylomemies. The resulting system will enrich a state-of-the-art tree like representation with the possibility to browse through the evolution of a corpus of documents at different level of observation, to interact with various scales of description, to reconstruct a hierarchical clustering of elements of knowledge and to navigate across complex semantic lineages. We will then formalize a generic macro-to-micro methodology of exploration and implement our system as a free software called the Memiescape. Our system will be illustrated by three use cases that will respectively reconstruct the scientific landscape of the top cited publications of the French CNRS, the evolution of the state of the art of knowledge dynamics visualization and the ongoing discovery process of Covid-19 vaccines.

Failures of Complex Systems

2021 ◽  
pp. 32-66
Author(s):  
William B. Rouse
Keyword(s):  
Complex Systems ◽  
Case Studies ◽  
Nuclear Power ◽  
Deepwater Horizon ◽  
Power Industry ◽  
Higher Order ◽  
Nuclear Power Industry ◽  
Maritime Industry ◽  
Space Operations ◽  
Multi Level

This chapter addresses failures in the nuclear power industry (Three Mile Island and Chernobyl), NASA space operations (Challenger and Columbia), and the maritime industry (Exxon Valdez and BP Deepwater Horizon). Multi-level analyses are used to provide comparisons across case studies. It briefly reviews how these industries anticipate and manage failures, and higher-order consequences of these types of failures are discussed. These insights are used to foreshadow later discussions of failure management.

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