Evolutionary Design Method Research Articles

Inspiring Designers’ Innovative Thinking: An Evolutionary Design Method for Product Forms

The product form serves as a crucial information carrier for expressing design concepts and encompasses significant valuable references. During the product iteration process, changes in design subjects, such as designers and decision-makers, result in substantial variability and uncertainty in the direction of product form evolution. To address these issues, an evolutionary design method for product forms based on the gray Markov model and an evolutionary algorithm is proposed in this study. Firstly, quadratic curvature entropy is utilized to quantify historical form features of product evolution. Subsequently, the original data on product form feature evolution are fitted and predicted using the gray Markov model, thereby obtaining the predicted value of the latest generation of product form features, which is determined to be 0.14586. Finally, this study uses this predicted value to construct a fitness function in the framework of an evolutionary algorithm, which in turn identifies next-generation product forms that can stimulate designers’ creative thinking. The method’s application is illustrated using the side outer contour of the Audi A4 automobile as an example. The research findings demonstrate that combining the gray Markov model with an evolutionary algorithm can effectively simulate designers’ understanding of previous generations’ design concepts and achieve stable inheritance of these design concepts during product iteration. This approach mitigates the risk of abrupt changes in design concepts caused by designers and decision-makers due to personal cognitive biases, thereby enhancing product development efficiency.

Evolutionary design method for transforming ceramic cultural elements into cultural and creative products

Cultural and creative products are empowered through cultural connotation in the market with ever-changing customer needs. Analyzing user preferences and matching them with product design elements has become the focus of research. Taking ceramic bracelet as the research example, this study proposed an evolutionary system which integrates the interactive genetic algorithm with artificial neural network and fuzzy analytic hierarchy process based on evaluation grid method. First, the cultural genes were extracted from cultural products as the design elements. Second, the attractiveness characteristics of the products and customer demand dimension information were analyzed by evaluation grid method. Third, the fuzzy analytic hierarchy process was used to assign weight values to the 3 users’ perceptual evaluation vocabularies. Fourth, the artificial neural network algorithm was incorporated into the fitness evaluation stage of the interactive algorithm to reduce information distortion caused by evaluation fatigue. Finally, after training the samples using the back propagation neural network, 8 design schemes with a fitness value exceeding 4.5 were obtained. The iterative curve indicated that after the 51st generation, the error accuracy approached 0.09. The experimental results verified that the system could help to improve the efficiency of product design, and design products that are more in line with user needs.

An Adaptive Evolutionary Neural Network-Based Optimization Design Method for Wideband Dual-Polarized Antennas

An Adaptive Evolutionary Neural Network-Based Optimization Design Method for Wideband Dual-Polarized Antennas

Evolution of Controllers Under a Generalized Structure Encoding/Decoding Scheme With Application to Magnetic Levitation System

Evolutionary search has been widely implemented for the adjustment of controllers’ parameters. Nevertheless, the structure of controllers, which has a more important role in control systems, has been seldom studied. To this end, an evolutionary design method of controllers is proposed to optimize both structures and parameters simultaneously in this article. A controller is made up of a combination of some basic controller components and relevant parameters. The design of controllers can be transformed into an optimization problem involving the structure (represented by discrete vectors) and parameters (represented by real numbers). A generalized structure encoding/decoding scheme is developed. Guided by the performance indicators, intelligent algorithms for both combinatorial and numerical optimization are employed to iteratively and cooperatively evolve the controller structure and parameters, respectively. In order to effectively reduce some redundant or infeasible solutions, a set of generation rules for the controller structure are put forward, which also ensures the feasibility of the structure. Furthermore, this method is applied to a magnetic levitation ball system with nonlinear dynamics and external disturbance. Both simulation and experiment results demonstrate the effectiveness and practicability of the proposed method.

Efficient artificial intelligence techniques for inverse design and knowledge discovery in metamaterials

A new artificial-intelligence (AI) approach based on dimensionality reduction techniques for the design and knowledge discovery in metamaterial structures will be presented. It is shown that reducing the dimensionality of the response and design spaces by using a pseudoencoder can reduce the computation time by 2–3 orders of magnitude. In addition, using pruning techniques can simplify the trained algorithm to further reduce the computation time while providing simpler paths for relating input-output relationships for understanding the role of design parameters (i.e., knowledge discovery). It is also shown that this approach can enable an evolutionary design method in which the initial design can be evolved intelligently into an alternative with favorable specifications. The application of these AI approaches for both optical and acoustic metamaterials will be presented.

Generative Design of Structured Materials for Controlled Frequency Responses.

Spatially varying material properties allow the dynamic response of structural systems to be almost arbitrarily tailored, far beyond the first or fundamental natural frequency. Continuing advances in manufacturing technology are making it possible to achieve the necessary range of stiffness and density variations, but the design of these property distributions is a challenging task because of the complex multidimensional nature of the problem. Generative design methods based on evolutionary optimization algorithms have been successfully used to obtain solutions based on multi-material distributions. However, the applicability of these solutions is limited by their reliance on multi-material additive manufacturing (AM), which currently only offers digitally mixed acrylic polymer options that are generally unsuitable to produce functional parts. A novel structured material solution is proposed here, in which the problem domain is divided into several volume elements (voxels), each of which contains a structure whose geometrical form is altered to adjust its effective properties to desired values. The single material structural solution will be amenable for ready fabrication by the powder-based selective laser sintering and melting processes with real engineering polymer and metal systems, thereby allowing for the realization of the benefits in real-world applications. The resulting continuous design spaces are searched using a modern evolutionary algorithm, the covariance matrix adaptation evolution strategy (CMA-ES). A MATLAB implementation of this evolutionary design method, in conjunction with finite element simulations for fitness evaluation, showed good convergence for several different cantilever beam test cases when tested against several different sets of target natural frequencies. Correlations with the multi-material solutions show that the single structured material approach is on par or even better in some cases, even though the test domain was discretized into 80% fewer voxels than for the multi-material case. Furthermore, the voxel structures can be realized using current AM technologies.

An Interactive Evolutionary Design Method for Mobile Product Customization and Validation of Its Application

Product customization is a means that effectively caters to personal needs, and as such, has increasingly caught the attention of both consumers and manufacturers. With technological advancements, the customization of products is now being made available through mobile applications. However, mobile apps need to be easy to use and operate, which presents some challenges for mobile app designers. In response, this study proposes an interactive evolutionary design method for mobile apps, based on an interactive genetic algorithm, to help consumers generate high-quality designs and enhance their retail experience by optimizing synthetic fitness and reducing the user’s fatigue from evaluation. Firstly, a human–computer interaction model for mobile interactive evolutionary design was launched to solve the screen space problem and simplify the evaluation process. Secondly, to accelerate the convergence of the algorithm, this paper combines hesitation patterns to obtain accurate individual fitness. Thirdly, an ongoing prediction and replacement mechanism were presented to improve user experience. After addressing these items, the proposed method is applied to a customization system that involves traditional brocade patterns of the Zhuang ethnic group in southwestern China and validated using a conventional interactive evolutionary design system with an interactive genetic algorithm. The experimental results show that the proposed method increases the designs’ efficiency, and can help consumers effectively customize their product purchases on mobile devices.

An evolutionary form design method based on aesthetic dimension selection and NSGA-II

Abstract In the era of rapid product update and intense competition, aesthetic design has been increasingly important in various fields, as aesthetic feelings of customers largely influence their purchase preferences. However, the quantification of aesthetic feeling is still a very subjective process due to vague evaluations. The determination of form parameters according to aesthetics is difficult hitherto. Aesthetic measure recently arises as a prominent tool for this purpose using formulas derived from aesthetic theory. But as revealed by existing studies, it needs to be customized with deterministic and objective methods to be reliable in practice use. To facilitate this application, this paper proposes an evolutionary form design method, integrating aesthetic dimension selection and parameter optimization. After summarizing initial aesthetic dimensions, aesthetic dimension selection based on expert decision-making and particle swarm optimization (PSO) is carried out. With filtered aesthetic dimensions, design parameters are optimized with NSGA-II (non-dominated sorting genetic algorithm). The quality of pareto solutions obtained to be design schemes is assessed by three criteria to conduct sensitivity analysis of cross and mutation probability and population size. Our experiment using bicycle form design shows that the proposed evolutionary form design method can generate numerous and variant aesthetic design schemes rapidly. This is very useful for both product redesign and innovative new product development.

Integrated multi-objective evolutionary optimization of production layout scenarios for parametric structural design of flexible industrial buildings

Due to product individualization, customization and rapid technological advances in manufacturing, production systems are faced with frequent reconfiguration and expansion. Industrial buildings that allow changing production scenarios require flexible load-bearing structures and a coherent planning of the production layout and building systems. Yet, current production planning and structural building design are mostly sequential and the data and models lack interoperability. In this paper, a novel parametric evolutionary design method for automated production layout generation and optimization (PLGO) is presented, producing layout scenarios to be respected in structural building design. Results of a state-of-the-art analysis and a case study are combined to develop a novel concept of integrated production cubes and the design space for PLGO as basis for a parametric production layout design method. The integrated production cubes concept is then translated into a parametric PLGO framework, which is tested on a pilot-project of a hygiene production facility to evaluate the framework and validate the defined constraints and objectives. Results suggest that our framework can produce feasible production layout scenarios, which respect flexibility and building requirements. In future research the design process will be extended by the development of a multi-objective evolutionary optimization process for industrial buildings to provide flexible building solutions that can accommodate a selection of several prioritized production layouts.

Evolutionary design of molecules based on deep learning and a genetic algorithm

Evolutionary design has gained significant attention as a useful tool to accelerate the design process by automatically modifying molecular structures to obtain molecules with the target properties. However, its methodology presents a practical challenge—devising a way in which to rapidly evolve molecules while maintaining their chemical validity. In this study, we address this limitation by developing an evolutionary design method. The method employs deep learning models to extract the inherent knowledge from a database of materials and is used to effectively guide the evolutionary design. In the proposed method, the Morgan fingerprint vectors of seed molecules are evolved using the techniques of mutation and crossover within the genetic algorithm. Then, a recurrent neural network is used to reconstruct the final fingerprints into actual molecular structures while maintaining their chemical validity. The use of deep neural network models to predict the properties of these molecules enabled more versatile and efficient molecular evaluations to be conducted by using the proposed method repeatedly. Four design tasks were performed to modify the light-absorbing wavelengths of organic molecules from the PubChem library.

An Evolutionary Design Method of Product Form Inspired by Spider-webs

Computer-Aided Design and Applications is an international journal on the applications of CAD and CAM. It publishes papers in the general domain of CAD plus in emerging fields like bio-CAD, nano-CAD, soft-CAD, garment-CAD, PLM, PDM, CAD data mining, CAD and the internet, CAD education, genetic algorithms and CAD engines. The journal is aimed at all developers and users of CAD technology to ptovide CAD solutions for various stages of design and manufacturing. The journal publishes all about Computer-Aided Design and Computer-Aided technologies.

Evolutionary Design Method for a Conducting Solid Cooled by Combined Free Convection and Radiation

Abstract An iterative design algorithm is used to adjust the shape of a conducting solid body that is subjected to a surface heat flux and cooled simultaneously by free convection and radiation in order to reduce the overall thermal resistance. Parametric simulations are carried out over a range of domain dimensions and emissivity values to determine the sensitivity of (i) the predicted solid shape and (ii) the overall thermal resistance to the relative strength of convection or radiation. Results show that, for the conditions considered, surface radiation has a significant influence on the predicted optimal solid geometry and overall thermal resistance.

New Biological Morphogenetic Methods for Evolutionary Design of Robot Bodies.

We present some currently unused morphogenetic mechanisms from evolutionary biology and guidelines for transfer to evolutionary robotics. (1) DNA patterns providing mutation of mutability, lead to canalization of evolvable bauplans, via kin selection. (2) Morphogenetic mechanisms (i) Epigenetic cell lines provide functional cell types, and identification of cell descent. (ii) Local anatomical coordinates based on diffusion of morphogens, facilitate evolvable genetic parameterizations of complex phenotypes (iii) Remodeling in response to mechanical forces facilitates robust production of well-integrated phenotypes of greater complexity than the genome. An approach is proposed for the tractable application of mutation-of-mutability and morphogenetic mechanisms in evolutionary robotics. The purpose of these methods, is to facilitate production of robot mechanisms of the subtlety, efficiency, and efficacy of the musculoskeletal and dermal systems of animals.

Research on Evolutionary Design Method of BIM Technology in Highway Reconstruction and Expansion Project

BIM technology is widely used in expressway Construction projects. In the process of transforming two-dimensional design into three-dimensional design, there are still many problems that need to be solved urgently. Based on the Beijing-Shanghai highway reconstruction and expansion project, this paper proposes an evolutionary design method. Based on the application standard of project model technology, the method uses BIM model software, based on skeleton lines and templates, using EKL programming language to realize the structure size from coarse to fine, information from summary to detail, and progressive design method for component granularity from bottom to high. At the same time, a three-dimensional design method for automatically generating road centerlines is proposed. The results show that the evolutionary design method is in line with the current project habits, matching the existing design concepts, and can efficiently complete the design work at different stages, effectively avoiding a lot of repetitive work.

Research on the construction of the spiral evolutionary design methodology for a product service system based on existing products

A product service system composed of products, services, hardware and software support, and stakeholders enhances the added value and competitiveness of products through resource integration. To reduce the input in servitization and improve feasibility, manufacturers tend to construct a product service system based on existing products to meet the demands of customers, instead of constructing a completely new product service system. Therefore, this article presents a spiral evolutionary design method to construct a product service system based on existing products. With the ultimate goal of the system evolution being the maximization of the use of existing products while satisfying the demands of customers, the system performance will be spirally upgraded under the guidance of the system evolution chain through the operation of the system symbiotic ring. The construction of a mobile fire extinguishing product service system based on existing fire-fighting equipment was used as an example to illustrate the feasibility of this methodology. Finally, a feasibility evaluation system was established to evaluate and compare the previous product service system methodologies with the methodology in this article.

Evolutionary design with freedom: Time dependent heat spreading

This paper illustrates the method of evolutionary design with freedom by considering the problem of determining the distribution of the thickness of a high-conductivity layer (heat spreader) installed on a conducting wall. Heating comes from a steady line source imposed at t = 0. Heat spreads in time-dependent fashion in two directions: longitudinally by conduction along the layer and the wall, and transversally by conduction through the wall and then by convection into the flow that cools the other side of the wall. The heat spreading has two regimes, which are dictated by the two diffusion time scales along the layer and across the wall. It is shown that the solution to the optimal heat spreader thickness problem is the parabolic profile, and it is the same in both regimes of time-dependent conduction.

User preference enabled intelligent 3D product evolutionary design

ABSTRACT3D modeling has been widely used in product design and is able to demonstrate design schemes intuitively. However, the process of developing a 3D model is complicated and users can hardly get involved. This paper proposed a user preference enabled 3D product evolutionary design method, which makes users capable of conducting the design processes. To do so, a series of 3D design schemes of a case product are created through parametric modeling. These parametric schemes are later coded as product chromosomes, of which the product form features are parametrized as product genes. To validate the proposed approach, simulation experiments are carried out involving various user groups with distinct preferences. According to the experiment results, the presented method allows the users without any design experiences to create their satisfied design schemes efficiently.

Literature Review of Evolutionary Hardware Application Based on Nios II and Neural Network

The development and research status of the evolutionary hardware technology are analyzed and summarized. The characteristics of the existing evolutionary circuit design methods are analyzed and compared. The genetic algorithm and other evolutionary control algorithms are analyzed, and the design method of the virtual reconfigurable circuit is studied. An evolutionary circuit design method of “Nios II+VRC array” is proposed, which has a wide range of applications and can be evolved from PC to online evolution.

Application of EEG and Interactive Evolutionary Design Method in Cultural and Creative Product Design.

In order to design a cultural and creative product that matched the target image, this paper proposed to use EEG, interactive genetic algorithm (IGA), and back propagation neural network (BPNN) to analyze the users' image preferences. Firstly, the pictures of cultural elements were grouped according to the pleasantness value and emotional state by PAD emotion scale, and the brain waves induced by the pictures of cultural elements with different pleasure degree were recorded by electroencephalograph. Then, the preference of cultural elements was obtained according to the theory of frontal alpha asymmetry. Secondly, the semantic difference method was used to carry out questionnaire survey to users, and the factor analysis method was used to statistically analyze the survey results to extract the perceptual image semantics of users for cultural and creative products. Thirdly, an interactive evolutionary design system based on IGA and BPNN was constructed. According to the cultural elements preferred by users, the designer designed the initial set of morphological characteristics, and the fitness value was determined according to the degree of user preference for the image semantics. Meanwhile, in order to reduce the fatigue caused by users' interaction evaluation, BPNN was introduced to simulate artificial evaluation. Finally, the proposed method was verified by the practice of flavoring bottle design. User preference requirement could be used as feedback information to help designers understand users' design emotional need and generate design schemes that satisfied the users' perceptual image.

Evolutionary design method of probabilistic finite state machine for swarm robots aggregation

This paper proposes to use evolutionary computations to determine the parameters of probabilistic finite state machine controllers for swarm robots. The robots are evolved to perform an aggregation task. This problem was formulated as an optimization problem and solved by the PSO. Several computer simulations were conducted to investigate the validity of the proposed method. The results obtained in this paper show us that the proposed method is useful for the aggregation problem and the best evolved controllers are feasible as well as interpretable. This would be transferable to real swarm robots problems.