Forthcoming articles


International Journal of System of Systems Engineering


These articles have been peer-reviewed and accepted for publication in IJSSE, but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.


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International Journal of System of Systems Engineering (7 papers in press)


Regular Issues


  • A study of an adaptive approach for systems-of-systems integration   Order a copy of this article
    by Ilyas Ed-daoui, Mhamed Itmi, Abdelkhalak El Hami, Nabil Hmina, Tomader Mazri 
    Abstract: Systems-of-systems are a growing composition of complex, autonomous and heterogeneous systems that collaborate in order to achieve complex and evolving targets that exceed the sum of the parts. In fact, the biggest challenge in such environment lays in the preservation of the viability of the system-of-systems and its evolvement while handling component systems dynamic integrations. This also represents a pressing issue in systems-of-systems engineering. In this paper, we present a collection of definitions dedicated to sire the system-of-systems concept, their characteristics and typology. Next, we detail the challenges facing the integration process in systems-of-systems. Then, we present our proposition to manage this issue. It is based on an adaptive integration approach to systems-of-systems typology. Two case studies are provided in order to experiment our theory. We evaluate the performance of the approach in both cases. Results are cross-compared.
    Keywords: interoperability; performance evaluation; simulation; systems-of-systems architecture; systems-of-systems integration.

  • Scoring the risk matrix   Order a copy of this article
    by Paul R. Garvey 
    Abstract: In systems engineering, the risk matrix is a popular protocol for binning risks into a collection of probability and consequence cells. In its traditional form, the risk matrix produces a ranking of cells according to their position in an ordered list. From this, management can distinguish whether a set of risks collected in one risk matrix cell has a higher priority than a set of risks collected in another cell. However, if decisions require measuring the relative differences between pairs of cells across their rank positions, then it is necessary to map them from their ordinal scale to an interval scale. This paper introduces methods from representational measurement theory to transform a rank ordered list of risk matrix cells into an interval measurement scale. The transformation produces a scored risk matrix. This allows relative differences among cells to be meaningfully compared, which broadens its use in management decisions. A scored risk matrix provides greater insights into the urgency of risks grouped within cells than is possible in a traditional risk matrix, while remaining within its ease and popularity of use.
    Keywords: systems engineering; engineering management; risk management; risk matrix; risk.

  • Spark! : An Integrated Resource Planning and Dispatch Tool for Power Grid Modelling   Order a copy of this article
    by Ange-Lionel Toba, Mamadou Seck 
    Abstract: The power grid infrastructure faces multiple challenges due to, not only the growing demands, but also the widespread deployment of renewable generation. The increasing level of renewable penetration in the energy mix requires to re-think the way the grid works, operates, and also how it is structured. This makes energy planning more critical as it will necessarily have to account for the effects of intermittence and variability of these sources, and the dynamic behavior of the overall system. Power grid models can play an important role in performing that task. What is needed, is a new, faster computational model that can simulate large-scale grid operations, while capturing generating units constraints, system flexibility and architecture. We present Spark!, a grid simulation model, for large scale future power grids over long term horizons. The model developed in Python, and built on a DEVS (Discrete Event System Specification) platform, captures the intermittent and stochastic nature of renewable energy resources and their associated forecast error, the thermal constraints of conventional generation resources, geographical and climate information, the transmission network, with a flexible time resolution.
    Keywords: Renewable Energy; Grid modelling; discrete-event; simulation.

  • Minimum variance control strategy for closed loop linear time invariant system   Order a copy of this article
    by Wang Jianhong 
    Abstract: To design one feedback controller in a closed loop linear time invariant system, the idea of minimum variance control is used to realize this goal. Two explicit forms corresponding to the closed loop system are considered, i.e. its general form and rational transfer function form respectively. Firstly one closed form solution of the minimum variance controller is derived in the general form of the closed loop linear time invariant system, and an optimization algorithm is proposed to obtain controller in practice. Secondly in the rational transfer function form of the closed loop linear time invariant system, the minimum variance controller is determined, while guaranteeing the modified variances of output and input as small as possible.
    Keywords: Minimum variance control; modified cost; Closed form solution; Alternating direction method of multipliers.

  • The Need for Simple Educational Case-studies to Show the Benefit of Soft Operations Research to Real-world Problems   Order a copy of this article
    by Andrew Collins, John Shull, Ying Thaviphoke 
    Abstract: Soft Operations Research (OR) methods have the potential to provide deep qualitative insights into the complex problems that face our world. However, the propagation of soft OR has, at best, stagnated in recent years and it has been rejected from mainstream academic hard (quantitative) OR. In this paper, it is proposed that there is a need for simple educational example that actually shows the benefit of soft OR. The paper suggests that these examples should be real-world case studies that do not include convoluted graphics or verbose prose descriptions. An example case study has been included in this paper. This case study investigates the impact of beer price changes to two virtually identical restaurant-bars in the Hampton Roads region of the United States. The case study shows that a simple quantitative analysis results in erroneous conclusions which could be avoided by conducting a simple qualitative analysis.
    Keywords: qualitative methods; soft operations research; problem structuring methods; restaurant revenue management; educational case studies.

Special Issue on: Soft Operations Research Methods for Complex Systems

  • Categorizing and clustering knowledge in Fuzzy Cognitive Maps   Order a copy of this article
    by Alexander Metzger, Steven Gray, Ellen Douglas, Paul Kirshen, Nardia Haigh 
    Abstract: The literature on managing environmental hazards in complex human-natural systems increasingly acknowledges the importance of integrating diverse stakeholder mental models into decision-making. Participatory Fuzzy Cognitive Mapping (FCM) provides an effective tool in this process, as it allows representation of mental models as complex causal networks that aid in the study of knowledge and understandings. While most participatory FCM research has studied mental model variation using graph theory and other structural metrics, our goal is to demonstrate a generalizable approach for analyzing perspectives and content. We use a novel method of knowledge categorization to identify variation among stakeholder mental models and explore its implications for social learning and collaboration. In our case study of flood managers in Boston, Massachusetts, our findings include identification of knowledge gaps, differing priorities among individuals and across jurisdictional scales and opportunities for learning and collaboration.
    Keywords: soft systems; fuzzy cognitive mapping; mental models; social-ecological systems; participatory modeling; environmental hazards; flooding; adaptive management; social learning; collaboration; knowledge clustering; knowledge categorization.

  • Using rich pictures outside of soft systems methodology: a case study analysis   Order a copy of this article
    by Tessa Berg, Simon Bell, Steve Morse 
    Abstract: The aim of this paper is twofold. Firstly we will highlight how a problem structuring tool, namely the Rich Picture, is being used across many disciplines outside of the soft system methodology which has historically been its home. Secondly, we highlight the controversial presence of non-conforming Rich Picture research and an apparent reluctance to publish from the systems community. In this paper we provide examples of rich picture research used independent from methodology and focus on one case study that uses a novel method of content analysis to appreciate the significance of the stories within their pictures. We demonstrate the theoretical justification and efficacy of an innovation in the assessment of the Rich Picture and its use as a tool to discern issues of importance across mixed groups. We discuss the responses to this work and the implications for innovation within soft OR research. We propose that the Rich Picture should not be seen as sacrosanct just because it derives from a well-established and much respected methodology. We argue that the Rich Picture can be a flexible space where any practitioner can negotiate shared understanding without methodological constraint.
    Keywords: rich picture; soft systems methodology; SSM; innovation; problem structuring.