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Retail design concepts are complex designs meeting functional and aesthetic demands from various constraint generators. However, the literature on this topic is sparse and offers only little support for store designers to deal with such challenges. To address this issue, the purpose of this paper is to identify the most important constraint generators, investigating the types of constraints they generate, and providing guidelines for how to deal with constraint elicitation.

The three contributions mentioned above are developed through discussions of the literature and eight case studies of fashion store design projects.

The paper shows that the influence of the constraint generators decreases during the design process except for supplier-generated constraints, which increase in the final stages of the design process. The paper argues that constraints should be elicited close to their occurrence, and that doing so requires a solid understanding of relevant constraint generators.

The paper provides a structured basis for further research and identifies areas warranting further study. Although, the paper’s focus is on fashion store design, the findings may, to some degree, be applicable to other types of store design projects.

The understandings provided by this paper may help designers to deal proactively with constraints, reducing the use of resources to alter design proposals.

The paper: defines the most important constraint generators from the perspective of retail store designers, clarifies the types of constraints they generate, and provides guidelines for how to deal with constraint elicitation.

This paper's objective is to explain the concept of proper kinematic constraint to guide requirements‐driven design of mechanical assemblies and to connects proper constraint to the datum flow chain (DFC) and key characteristics (KCs).

The paper presents proper constraint as a way to support the goal of placing key parts in particular geometric relationships with respect to one another so that a DFC can deliver KCs unambiguously. Such a DFC is said to be competent. Additionally, a competent DFC is robust in the sense that the constraint relationships between parts retain their definition and effect under all allowed variations in parts.

Failure to provide proper constraint can lead to undesired consequences including locked‐in stresses and difficult or inconsistent assembly. Some designs need to be over‐constrained, and this requires very careful control and tight tolerances on the over‐constrained degrees of freedom in order to avoid or at least understand the consequences listed above.

Mathematical methods exist to test designs for proper constraint. The simplest, and occasionally unsuccessful, is the Kutzbach criterion. Screw theory is the most reliable method but its application requires extra knowledge and mathematical tools.

Most CAD software and tolerance analysis software do not test designs for their state of constraint. The engineer needs to take account of this independently and be aware of the limitations of software as a guide. Tolerance analysis software that does not take account of constraint may yield incorrect answers.

The paper reinvigorates a once‐well‐known principle and makes engineers aware of it. It also links this concept to the concepts of DFC and KCs and supports a mathematically‐based method for designing assemblies.

Existing models of product assembly scheme design often ignore the constraint relations among design thinking. In order to grasp the functions of each part and the constraint relations among them in product assembly system macroscopically, further design and variation of product assembly system should be made according to design thinking. This paper seeks to address these issues.

Through analyzing the similarity between biological organization system and product system and taking biology knowledge for reference, product assembly system was expressed as product function gene, product constraint gene, product function protein, product constraint protein and product cell and so on in this paper. The product gene model composed of product function gene groups and constraint genes was established and a modeling method based on it was proposed.

The author applied this method to model the 5‐DOF manipulator of complex diamond manufacturing special equipment with good results which proved the effectiveness of this modeling method.

By identifying constraint relations and design thinking in the gene model, the system makes the modification process which is conducted by the designers automatically identified and varied to achieve computer‐aided design and assembly.

The structural design problem can be viewed as an iterative design loop with each iteration involving two stages for topology and shape designs with genetic algorithm (GA) as the optimization tool for both.

The topology optimization problem, which is ill posed, is regularized using a constraint on perimeter and solved using GA. The problem is formulated as one of compliance minimization subject to volume constraint for the single loading case. A dual formulation of this has been used for the multiple loading cases resulting in as many behavioral constraints as there are loading cases. The tentative topology given by the topology optimization module is taken and the domain boundary is approximated using straight lines, B‐splines and cubic spline curves and design variables are selected among the boundary defining points. Optimum boundary shape of the problem has been obtained using GA in two different ways: without stress constraints; and with stress constraints.

The proposed two stage strategy has been tested on benchmark structural optimization problems and its performance is found to be extremely good.

The strategy appears to be eminently suitable for implementation in a general purpose FE software as an add‐on module for structural design optimization.

It has been observed that the integrated topology and shape design method is robust and easy to implement in comparison with other techniques. The computing time requirements for the GA does not appear daunting in the present scenario of high performance parallel computing and improved GA techniques.

The use of three non‐linear mathematical programming techniques for the optimization of structural design problems is discussed. The methods — sequential linear programming, the feasible direction method and the sequential unconstrained minimization technique — are applied to a portal frame problem to enable a study of their convergence efficiency to be studied. These methods are used for both the sizing of the structural members and determining the optimum roof pitch. The sequential linear programming method is shown to be particularly efficient for application to structural design problems. Some comments on the development of computer software for structural optimization are also given.

Several frameworks of retail store environment variables exist, but as shown by this paper, they are not particularly well-suited for supporting fashion store design processes. Thus, in order to provide an improved understanding of fashion store design, the purpose of this paper is to identify the most important store design variables, organise these variables into categories, understand the design constraints between categories, and determine the most influential stakeholders.

Based on a discussion of existing literature, the paper defines a framework of store design variables and constraints between these. The framework is investigated through six case studies of fashion store design projects.

Through a discussion of literature and empirical studies, the paper: identifies the most important store design variables, organises these variables into categories, provides an understanding of constraints between categories of variables, and identifies the most influential stakeholders. The paper demonstrates that the fashion store design task can be understood through a system perspective, implying that the store design task becomes a matter of defining a set of subsystems, while considering their mutual interdependencies.

The proposed framework may be used as a point of departure and a frame of reference for future research into fashion store design.

The paper may support retail designers and retail managers in fashion store design processes by clarifying which store design variables to consider and providing an understanding of the constraints between them.

The perspective on the fashion store design task offered by the proposed framework adds a layer of understanding to the way in which existing literature describes the challenges related to store design. The empirical studies of fashion store projects demonstrate that the described system perspective offers a useful way of organising fashion store designers’ experiences from design processes.

Meta-model method has been widely used in structural reliability optimization design. The main limitation of this method is that it is difficult to quantify the error caused by the meta-model approximation, which leads to the inaccuracy of the optimization results of the reliability evaluation. Taking the local high efficiency of the proxy model, this paper aims to propose a local effective constrained response surface method (LEC-RSM) based on a meta-model.

The operating mechanisms of LEC-RSM is to calculate the index of the local relative importance based on numerical theory and capture the most effective area in the entire design space, as well as selecting important analysis domains for sample changes. To improve the efficiency of the algorithm, the constrained efficient set algorithm (ESA) is introduced, in which the sample point validity is identified based on the reliability information obtained in the previous cycle and then the boundary sampling points that violate the constraint conditions are ignored or eliminated.

The computational power of the proposed method is demonstrated by solving two mathematical problems and the actual engineering optimization problem of a car collision. LEC-RSM makes it easier to achieve the optimal performance, less feature evaluation and fewer algorithm iterations.

This paper proposes a new RSM technology based on proxy model to complete the reliability design. The originality of this paper is to increase the sampling points by identifying the local importance of the analysis domain and introduce the constrained ESA to improve the efficiency of the algorithm.

The purpose of this paper is to propose an effective and efficient numerical method that can consider natural frequency in multi-material topology optimization (MMTO) and which is scalable for complex three-dimensional (3D) problems.

The optimization algorithm is developed by combining custom FORTRAN code for MMTO with the open-source software Mystran, which is used as a finite element analysis (FEA) solver. The proposed algorithm allows the designer to shift the fundamental frequency of the design beyond a defined frequency spectrum from the initial designing phase. The methodology is formulated in a smooth and differentiable manner, with the sensitivity expressions, required by gradient-based optimization solvers, presented.

Natural frequency constraint has been successfully implemented into MMTO. The use of open-source software Mystran as an FEA solver in the algorithm provides ability to solve complex problems. Mystran offers powerful built-in functions for eigenvalue extraction using methods like Givens, modified Givens, inverse power and the Lanczos method, which provide the ability to solve complex models. The algorithm is successfully able to solve both two- and three-material MMTO jobs for two-dimensional and 3D geometries.

Natural frequency constraint consideration into topology optimization is very challenging due to three common issues: localized eigenmodes, mode switching and high computational cost. The proposed algorithm addresses these inherent issues, implements natural frequency constraint to MMTO and solves for complex models, which is hardly possible using conventional methods.

This paper demonstrates the use of genetic algorithms (GAs) for size optimization of trusses. The concept of rebirthing is shown to be considerably effective for problems involving continuous design variables. Some benchmark examples are studied involving 4‐bar, 10‐bar, 64‐bar, 200‐bar and 940‐bar two‐dimensional trusses. Both continuous and discrete variables are considered.

In this article, a practical design methodology is proposed for discrete sizing optimization of high-rise concrete buildings with a focus on large-scale and real-life structures.

This framework relies on a computationally efficient approximation of the constraint and objective functions using a radial basis function model with a linear tail, also called the combined response surface methodology (RSM) in this article. Considering both the code-stipulated constraints and other construction requirements, three sub-optimization problems were constructed based on the relaxation model of the original problem, and then the structural weight could be automatically minimized under multiple constraints and loading scenarios. After modulization, the obtained results could meet the discretization requirements. By integrating the commercially available ETABS, a dedicated optimization software program with an independent interface was developed and details for practical software development were also presented in this paper.

The proposed framework was used to optimize different high-rise concrete buildings, and case studies showed that material usage could be saved by up to 12.8% compared to the conventional design, and the over-limit constraints could be adjusted, which proved the feasibility and effectiveness.

This methodology can therefore be applied by engineers to explore the optimal distribution of dimensions for high-rise buildings and to reduce material usage for a more sustainable design.