Abstract
Systems engineering is an ubiquitous discipline of Engineering overlapping industrial, chemical, mechanical, manufacturing, control, software, electrical, and civil engineering. It provides tools for dealing with the complexity and dynamics related to the optimisation of physical, natural, and virtual systems management. This paper presents a review of how multi-agent systems and complex networks theory are brought together to address systems engineering and management problems. The review also encompasses current and future research directions both for theoretical fundamentals and applications in the industry. This is made by considering trends such as mesoscale, multiscale, and multilayer networks along with the state-of-art analysis on network dynamics and intelligent networks. Critical and smart infrastructure, manufacturing processes, and supply chain networks are instances of research topics for which this literature review is highly relevant.
Highlights
Systems engineering is an amalgamation of engineering disciplines for the design, control, and overall management of the life cycle of engineered systems from an interdisciplinary point of view [1]
This paper presents the essentials of complex networks and multi-agent systems (MAS) for control and optimisation in systems engineering
Other researchers use the notion of agency to distinguish between two types of agents: those that exhibit properties attributed to hardware and software systems, i.e., autonomy, social ability, reactivity, and pro-activeness, and those that exhibit properties normally attributed to humans, e.g., based mental or emotional notions such as knowledge [113]
Summary
Systems engineering is an amalgamation of engineering disciplines for the design, control, and overall management of the life cycle of engineered systems from an interdisciplinary point of view [1]. Each component of the system works towards individual and collective objectives to optimise local and general performance objectives This decision-making process of each component can be modelled by multi-agent systems (MAS) [4,5]. Intelligent distributed systems are capable of modelling how different parts of the network might work individually and collectively [10] This is used as support for any decision-making system aiming to achieve better overall system functioning and its consequent performance.
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