Infrastructure resilience to navigate increasingly uncertain and complex conditions in the Anthropocene

Infrastructure are at the center of three trends: accelerating human activities, increasing uncertainty in social, technological, and climatological factors, and increasing complexity of the systems themselves and environments in which they operate. Resilience theory can help infrastructure managers navigate increasing complexity. Engineering framings of resilience will need to evolve beyond robustness to consider adaptation and transformation, and the ability to handle surprise. Agility and flexibility in both physical assets and governance will need to be emphasized, and sensemaking capabilities will need to be reoriented. Transforming infrastructure is necessary to ensuring that core systems keep pace with a changing world.

The future of complexity engineering

Complexity Engineering encompasses a set of approaches to engineering systems which are typically composed of various interacting entities often exhibiting self-* behaviours and emergence. The engineer or designer uses methods that benefit from the findings of complexity science and often considerably differ from the classical engineering approach of “divide and conquer”.This article provides an overview on some very interdisciplinary and innovative research areas and projects in the field of Complexity Engineering, including synthetic biology, chemistry, artificial life, self-healing materials and others. It then classifies the presented work according to five types of nature-inspired technology, namely: (1) using technology to understand nature, (2) nature-inspiration for technology, (3) using technology on natural systems, (4) using biotechnology methods in software engineering, and (5) using technology to model nature. Finally, future trends in Complexity Engineering are indicated and related risks are discussed.

Human-computer co-operative co-evolutionary method and its application to a satellite module layout design problem

The layout design of a satellite module is a complex mechanical layout problem. Its main difficulties lie in combinatorial explosion of computational complexity, engineering complexity, and applicability in engineering practice. Inspired by the human-computer cooperation ideas, a human–computer co-operative co-evolutionary method for optimising layout design of a satellite module is developed. This method constructs the diversity reference set by using the diversity intelligence solutions (DIs) that are created by using the combinatorial operators of differential evolution (DE) and the blend crossover operator (BLX-a). During the co-evolution process of the presented method, the AIs, the DIs and the algorithm solutions are expressed by unified encoding strings and incorporated together to create new co-operative solutions. An instance of a satellite module layout design is presented to demonstrate the feasibility and effectiveness of the proposed method. Compared with the co-evolutionary approach and the all-at-once optimisation approaches, computational results show that the proposed method not only can produce better solutions, but also can better balance the conflicting objectives on the trade-off issues.