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An automated fully stressed design approach based on the Xie and Steven algorithm is presented. With this algorithm a fully stressed design is obtained by a gradual removal of low stressed material. By applying this evolutionary procedure a layout or topology of a structure can be found from an initial block of material. A fully integrated, interactive program is presented which incorporates automatic mesh generation, finite element analysis and the fully stressed design algorithm. The feasibility of the approach is demonstrated using several examples.

What has been called “the McDonaldization of universities” (another name for top-down and strong corporate managerialism) has gained momentum as a model for governing and managing universities. This trend exacerbates the traditional tension between academic freedom and managerial control – a major challenge for the administration of academic institutions. The ideas of Charles Darwin represent an opportunity for overcoming such a challenge. However, traditional managerial models show inadequate, pre-Darwinian assumptions for devising organizational designs. This paper aims to show not only the opportunities but also the challenges of embracing a Darwinian paradigm for designing social systems. The case of managerialism in universities is an illustrative example. The paper proposes evolutionary guidelines for designing universities capable of maintaining managerial control while warranting academic freedom.

The paper proposes to understand the tension between academic freedom and managerial control in universities as the same tension between freedom and control that Karl Popper identified as successfully handled by evolutionary processes. The paper uses Darwinian theory, understood as a broader theory for complex systems, as a heuristic for designing social systems – universities in this case – able to adapt to changing environmental conditions while handling equilibrium between freedom and control. The methodology articulates the Popperian model of knowledge with the Darwinian scheme proposed by David Ellerman known as “parallel experimentation” for suggesting organizational forms in which university administrators and faculty can interact for generating free innovations in pseudo-controlled organizational arrangements.

A salient characteristic of strong managerialism is its pre-Darwinian understanding of survival and adaptation; such an approach shows important flaws that can lead universities to unfit designs that changing environments can select for elimination. As an alternative, the philosophy behind the ideas of Charles Darwin provides guidelines for designing innovative and adaptive social systems. Evolutionary principles challenge basic tenets of strong managerialism as Darwinian designs discard the possibility of seeing managers as knowledgeable designers that allegedly can avoid mistakes by allocating resources to “one-best” solutions through ex ante exhaustive, top-down control. Instead, a Darwinian model requires considering survival as a matter of adaptability through continuous experimentation of blind trials controlled by ex post selection. The key is to organize universities as experimenting systems that try new and different things all the time and that learn and improve by making mistakes, as an adaptive system.

Governing and managing universities require to acknowledge the uniqueness of academic institutions and demand to look for appropriate forms of organization. The proposal of this paper opens possibilities for exploring and implementing action-research initiatives and practical solutions for universities. Studies in management and administration of higher-education institutions must take into account the characteristics of this type of organizations and should consider wider spectrums of possibilities beyond the core ideas of managerialism.

University managers face a special challenge for achieving equilibrium between managerial control and academic freedom. Darwinian models of management invite to reconsider several management creeds, for instance, that “errors are bad things” – instead of innovation triggers and learning opportunities or that “one solution must fit all” – instead of considering bottom-up, different and adaptive solutions triggered by local academic units, each facing different environments.

Currently, there is no clear picture for governing universities. This paper introduces principles and guidelines for facing the current challenge that strong managerialism represents if universities are expected to maintain academic freedom and also survive in volatile environments.

This article aims to provide a brief overview of the field now known as “evolutionary developmental robotics (evo-devo-robo)”, which is based on the concept and principles of evolutionary and development principles such as evolutionary developmental psychology, evolutionary developmental biology (evo-devo) and evolutionary cognitive neuroscience.

Evo-devo-robo is a new field bringing together developmental robotics and evolutionary robotics to form a new research area. Basic concepts and the origins of the field are described, and then some basic principles of evo-devo-robo that have been developed so far are discussed.

Finally, some misunderstand concepts and the most promising future research developments in this area are discussed.

Basic concepts and the origins of the field are described, and then some basic principles of evo-devo-robo that have been developed so far are discussed. Finally, some misunderstood concepts and the most promising future research developments in this area are discussed.

The paper seeks to make a substantial contribution to the still controversial question of design foundations.

A generic hypercyclic design process model is derived from basic notions of evolution and learning in different domains of knowing (and turns out to be not very different from existing ones). The second‐order cybernetics and evolutionary thinking provide theoretical support.

The paper presents a model of designerly knowledge production, which has the potential to serve as a genuine design research paradigm. It does not abandon the scientific or the hermeneutic or the arts & crafts paradigm but concludes that they have to be embedded into a design paradigm. “Design paradigm” means that “objects” are not essential, but are created in communication and language.

Foundations cannot be found in the axiomatic statements of the formal sciences, nor in the empirical approaches of the natural sciences, nor in the hermeneutic techniques of the humanities. Designing explores and creates the new; it deals with the fit of artefacts and their human, social and natural contexts. Therefore foundations for design (if they exist at all) have to be based on the generative character of designing, which can be seen as the very activity which made and still makes primates into humans.

The hypercyclic model provides a cybernetic foundation (or rather substantiation) for design, which – at the same time – serves as a framework for design and design research practice. As long as the dynamic model is in action, i.e. stabilized in communication, it provides foundations; once it stops, they dissolve. The fluid circular phenomena of discourse and communication provide the only “eternal” essence of design.

“Design objects” as well as “theory objects” are transient materializations or eigenvalues in these circular processes. Designing objects and designing theories are equivalent. “Problems” and “solutions” as well as “foundations” are objects of this kind. This contributes to a conceptual integration of the acting and reflecting disciplines.

The purpose of this paper is to study the problem of a routing problem with uncertain try-on service time (VRPUS) for apparel distribution, and to devise solution strategies coping with the uncertainty by an evolutionary algorithm. VRPUS belongs to the category of practical routing models integrated with uncertain service times. However, in the background of apparel distribution, it has distinct features. The try-on service will improve the customer satisfaction by providing experiences to customers; the return cost is saved; the customer loyalty is improved for experiencing face-to-face try-on services. However, the uncertainty of try-on service time makes the apparel distribution process uncertain and incurs additional risk management cost, such that the logistics companies should optimally make decisions on the choice of the service and the service processes.

This paper devised a mixed-integer programming (MIP) model for the base vehicle routing problem (VRP) and then it is extended to support the solution strategies for uncertain try-on times. A try-on time estimation parameter and a time reservation parameter are used to cope with the uncertain try-on time, and the try-on rejection strategy is applied when the uncertain try-on time is realized at customer and no surplus time can be used for try-on service besides distributing to remainder customers. Due to the computational complexity of VRPUS, an evolutionary algorithm is designed for solving it. These parameters and strategy options are designed for the operational decisions by logistics companies. Finally, a decision support system (DSS) is designed.

Five experimental scenarios are performed to reveal the impacts of parameters and solution strategies coping with uncertain try-on time on the distribution cost, return cost, and the try-on service failure. The tuning methods are designed to assist the decisions by logistics companies.

A new routing problem is addressed for apparel distribution in fashion industry especially in the context of booming apparel e-commerce, which is a VRP with uncertain try-on service time for apparel distribution; three strategies are developed to cope with the try-on time uncertainty. The proposed method is also a theoretical base for designing a practical DSS for logistics companies to provide try-on service to customers.

In today’s changing world, knowledge, and the processes to generate it and manage it, have become key factors in creating competitive business advantage. However, the challenges facing contemporary global societies, from human conflicts to environmental degradation, call for an expanded research agenda in the field of knowledge management. Issues such as improvement of the role of corporate citizenship to promote socially and ecologically responsible operations and development of human and social capital should become part of a purposeful strategy for creating a better future. “Knowledge is power” – and it is up to those with access to knowledge to decide if that power will continue to be used over others to increase the gap between rich and poor or if it will be a power to empower visions and realities based on an inclusive planetary ethic. From an evolutionary systems perspective, this paper explores some of the implications and key contributions that knowledge management can make for the transition toward sustainable forms of social organization. The heuristic of evolutionary learning community (ELC) is presented as a participatory strategy for promoting learning and knowledge creation for evolutionary development.

This paper aims to describe colonial competitive algorithm (CCA), a novel socio‐politically inspired optimization strategy, and how it is used to solve real world engineering problems by applying it to the problem of designing a multivariable proportional‐integral‐derivative (PID) controller. Unlike other evolutionary optimization algorithms, CCA is inspired from a socio‐political process – the competition among imperialists and colonies. In this paper, CCA is used to tune the parameters of a multivariable PID controller for a typical distillation column process.

The controller design objective was to tune the PID controller parameters so that the integral of absolute errors, overshoots and undershoots be minimized. This multi‐objective optimization problem is converted to a mono‐objective one by adding up all the objective functions in which the absolute integral of errors is emphasized to be reduced as long as the overshoots and undershoots remain acceptable.

Simulation results show that the controller tuning approach, proposed in this paper, can be easily and successfully applied to the problem of designing MIMO controller for control processes. As a result not only was the controlled process able to significantly reduce the coupling effect, but also the response speed was significantly increased. Also a genetic algorithm (GA) and an analytical method are used to design the controller parameters and are compared with CCA. The results showed that CCA had a higher convergence rate than GA, reaching to a better solution.

The proposed PID controller tuning approach is interesting for the design of controllers for industrial and chemical processes, e.g. MIMO evaporator plant. Also the proposed evolutionary algorithm, CCA, can be used in diverse areas of optimization problems including, industrial planning, resource allocation, scheduling, decision making, pattern recognition and machine learning.

The purpose of the study is to propose a framework for understanding the dynamism of the human self-system from evolutionary and socio-psychological perspective. The study aims to help scholars interested to use an evolutionary lens for examining consumer behaviour.

Relying on the principle of self-cybernetics, the study proposed a general framework explaining the operating mechanism of human self-system. The proposed framework incorporates the socio-psychological and the evolutionary perspective of the human self-concept.

The framework may help consumer scholars to integrate socio-psychological and evolutionary theories to produce novel and testable hypotheses.

To the best of the authors’ knowledge, this is the first attempt to propose a framework based on the principle of cybernetics to facilitate the use of an evolutionary lens in consumer research.

This paper aims to describe an integrated hardware/software system based on evolutionary robotics and its application in an edutainment context.

The system is based on a wide variety of artificial life techniques (artificial neural networks, genetic algorithms, user‐guided evolutionary design and evolutionary robotics). A user without any computer programming skill can determine the robot's behavior in two different ways: artificial breeding or artificial evolution. Breedbot has been used as a didactic tool in teaching evolutionary biology and as a “futuristic” toy by several science centers. The digital side of Breedbot can be downloaded on the web site: www.isl.unina.it/breedbot Findings – The results in this pilot study suggest that using Breedbot in an educational context can be useful to improve learning in biology.

As this is a pilot study, one limitation is the small sample considered. The issue will be investigated further with a wider population and subject‐matter, which will also improve the Breedbot system.

These results suggest that tools like Breedbot could be introduced into biology curricula at schools.

The paper describes an original application in digital content and shows the importance of using such a tool in an Edutainment context. It is therefore interesting for teachers, vocational trainers and anyone involved in educational activities.

The purpose of this paper is to find optimal solutions for conceptual design automation, which can be integrated with Building Information Modelling (BIM) support for construction automation. Problems relating ostensibly to failures in computational support for the conceptual design stage are well-documented in extant literature. These failures are multifarious and significant, with several deficiencies being acknowledged in the Architecture, Engineering, and Construction (AEC) industry. Whilst acknowledging this, extant literature has highlighted the importance of computational design in the AEC industry; and failures in this area include the need to strengthen the congruent links and support mechanisms in order to exploit the opportunities presented by new computational design methods. Given this, it is postulated that the application of generative design could enhance the design experience by assisting designers with the iterative generation of alternatives and parameterisation (change management) processes. Moreover, as BIM applications are increasingly providing comprehensive support for modelling and management, then additional synergies could be examined for further exploitation.

This paper focusses on the potential for developing an interactive BIM environment that purposefully adopts generative design as a method of computational design for the early design stages. This research facilitates the automation of the conceptual architectural design process, using BIM as the central conduit for enhancing the integration of the whole building design process (including design interfaces). This approach is designed to improve designers’ cognition and collaboration during the conceptual architectural design process.

This paper evaluates the existing methods and decision support mechanisms, and it introduces the potential of combining different concepts into a single environment (generative design/BIM).

This research is novel, in that it critically appraises virtual generative workspaces using BIM as the central conduit. The outcome and intervention of this research forms a theoretical basis for the development of a “proof of concept” prototype, which actively engages generative design into a single dynamic BIM environment to support the early conceptual design process.