Configuring advanced evolutionary algorithms for multicriteria building spatial design optimisation

Blom, Koen van der; Boonstra, Sjonnie; Hofmeyer, H.; Bäck, Thomas; Emmerich, Michael

doi:10.1109/cec.2017.7969520

Cited by 7 publications

(5 citation statements)

References 18 publications

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“…In the near future, a multi-disciplinary design modification will be developed based on simulations of co-evolutionary design processes. Subsequently an optimisation approach will be developed where both representations are used alternately: The super-structured approach will allow a dedicated optimisation algorithm to find a global optimum [40,42], whereas this solution in a super-structure free approach can be used by the developed design modification to explore more freely another (possibly local) optimum. As such the design space is cyclically both explored in-depth (via the super-structure) and globally (via the super-structure free representation).…”

Section: Discussionmentioning

confidence: 99%

“…The toolbox has been applied in [40,41,42], where also evolutionary algorithms were employed to find optimal building spatial design configurations. Moreover an elementary implementation of a simulation of co-evolutionary design processes has been presented to demonstrate the use and versatility of the toolbox and also to show the promises and the challenges of this method.…”

Section: Discussionmentioning

confidence: 99%

“…The presented work shows the promise of simulations of co-evolutionary design processes over a super-structured approach, but it also shows the challenges that should still be overcome. Only superstructure free optimisation is demonstrated here, application of the toolbox in super-structured optimisation can be found in [40,41,42,43], in which the supercube representation is used with a multi-disciplinary evolutionary optimisation algorithm to optimise for structural performance and building surface area.…”

Section: Toolbox Demonstrationmentioning

confidence: 99%

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Toolbox for super-structured and super-structure free multi-disciplinary building spatial design optimisation

Boonstra¹,

Blom

Hofmeyer³

et al. 2018

Advanced Engineering Informatics

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Toolbox Demonstrationmentioning

confidence: 99%

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Toolbox for super-structured and super-structure free multi-disciplinary building spatial design optimisation

Boonstra¹,

Blom

Hofmeyer³

et al. 2018

Advanced Engineering Informatics

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“…Since the hybridization methodology combines more than one optimization platform into a new one in which it inherits its pros/advantages and minimizes its cons/disadvantages. This requires special improvements of the existing hybrid optimization approaches responding to unique requirements of energy-efficient design performance simulations in the early stages of building constructions, with a particular focus on (a) improving the initialization and mutation operations of the tailored algorithms and other stochastic-based algorithms so that all parts of design search spaces (a portfolio of all possible design solutions) can be effectively explored; (b) investigating hybridization schemes, in a case of combining tailored algorithms (e.g., S-Metric-Selection-Evolutionary-Multi-objective-Optimization Algorithms [168][169][170], etc.) with methods of simulating evolutionary design process (simulation model evaluation function) with the aim of achieving more realistic designs [171]; (c) developing new sub-processes for the hybrid used as algorithms to define new super-design shapes/variants based on a collection of possible solutions instead of just one solution or include solutions found through voluntary design process simulations that utilize design rules, in addition to allowing the building design to include more disciplines, such as cooling and lighting; and (d) investigating the sensitivity of the hybrid approaches to the stochastic nature of tailored algorithms (including the challenges related to optimization algorithms, which occur when integrated with design performance simulation tools), along with the applicability of modifying hybridization schemes to reduce that sensitivity.…”

Section: Future Research Directionsmentioning

confidence: 99%

Performance Optimization Studies on Heating, Cooling and Lighting Energy Systems of Buildings during the Design Stage: A Review

et al. 2021

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Optimizing the building performance at the early design stage is justified as a promising approach to achieve many sustainable design goals in buildings; in particular, it opens a new era of attractive energy-efficient design for designers and architects to create new building constructions with high-energy efficiency and better overall performance. Accordingly, this study aims to provide a comprehensive review of performance optimization studies on heating, cooling, and lighting energy systems of buildings during the design stages, conducting a systematical review covering various aspects ranging from the building type, optimization inputs, the approach used, and the main conclusion. Furthermore, the benefits and limitations of early optimizations in the energy-efficient design performance of buildings and future research directions are identified and discussed. The review results show that previous research efforts of optimizing energy-efficient design performance in buildings have addressed a wide variety of early stage design optimization issues, including orientation and multi-objective building function-related conflicts, such as cooling and lighting. However, significant research issues related to investigations of design envelope materials, proper energy-efficient design form, and other passive parameters, such as solar photovoltaic systems, are still lacking. Therefore, future research should be directed towards improving existing optimization approach frameworks in the context of appropriate energy-efficient design features; integrating sensitivity and uncertainty analyses in the performance optimization framework of buildings to provide a more balanced assessment of influential design envelope properties and extending optimal design envelope investigations of buildings to include other passive parameters and lifecycle assessment under long-term weather conditions.

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“…And, in Refs. [48][49][50] evolutionary algorithms are applied and configured to building spatial design optimization. Furthermore, in Ref.…”

Section: Motivationmentioning

confidence: 99%

Conceptual structural system layouts via design response grammars and evolutionary algorithms

Boonstra

Blom

Hofmeyer

et al. 2020

Automation in Construction

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Two new methods to generate structural system layouts for conceptual building spatial designs are presented. The first method, the design response grammar, uses design rules-configurable by parameters-to develop a structural system layout step by step as a function of a building spatial design's geometry and preliminary assessments of the structural system under development. The second method, design via optimizer assignment, uses an evolutionary algorithm to assign structural components to a building spatial design's geometry. In this work, the methods are demonstrated for two objectives: minimal strain energy (a commonly used objective for structural topology optimization) and minimal structural volume. In a first case study three building spatial designs have been subjected to the methods: Design via optimizer assignment yields a uniformly distributed Pareto front approximation, which incorporates the best performing layouts among both methods. On the other hand, results of the design response grammar show that layouts that correspond to specific positions on the Pareto front (e.g. layouts that perform well for strain energy), share the same parameter configurations among the three different building spatial designs. By generalizing, specific points on the Pareto front approximation have been expressed in terms of parameter configurations. A second case study addresses the use of a generic material and generic dimensions in the assessment of structural system layouts. The study applies a technique similar to topology optimization to optimize the material density distribution of each individual structural component, which can be regarded as a part of determining materials and dimensions in more advanced stages of the design of a system layout. This optimization approach is applied to the layouts that are part of the Pareto front approximations as found by the evolutionary algorithm in the first case study, the study shows that-after optimization-the fronts remain the same qualitatively, suggesting that the methods produce results that are also useful in more advanced design stages. A final case study tests the generalization that is established in the first case study by using the found configurations for the design response grammar, and it is shown that the generated layouts indeed are positioned near the desired positions on the Pareto front approximation found by the evolutionary algorithm. Although the evolutionary algorithm can find better performing solutions among a better distributed Pareto front approximation, the design response grammar uses only a fraction of the computational cost. As such it is concluded that the design response grammar is a promising support tool for the exploration and structural assessment of conceptual building spatial designs. Future research should focus on more types of structural elements; more objectives; new constraints to ensure feasible solutions, especially stress constraints; and the application of state-of-the-art techniques like machine learning to find more general...

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Configuring advanced evolutionary algorithms for multicriteria building spatial design optimisation

Cited by 7 publications

References 18 publications

Toolbox for super-structured and super-structure free multi-disciplinary building spatial design optimisation

Toolbox for super-structured and super-structure free multi-disciplinary building spatial design optimisation

Performance Optimization Studies on Heating, Cooling and Lighting Energy Systems of Buildings during the Design Stage: A Review

Conceptual structural system layouts via design response grammars and evolutionary algorithms

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