Browsing by Author "Chatzikonstantinou, Ioannis"

Now showing 1 - 19 of 19

Citation - WoS: 11
Citation - Scopus: 13
A 3-Dimensional Architectural Layout Generation Procedure for Optimization Applications: DC-RVD
(Education and research in Computer Aided Architectural Design in Europe, 2014) Ioannis Chatzikonstantinou; Chatzikonstantinou, Ioannis; E.M. Thompson
A procedure for generating 3-dimensional spatial configurations for optimization applications termed Dimension Constrained Rectangular Voronoi Diagram (DC-RVD) is presented in this paper. The procedure is able to generate a non-overlapping configuration of spatial units in 3-dimensional space given a string of real values. It constitutes an extension and adaptation of the Rectangular Voronoi Diagram generating procedure found in the work of Choi and Young (1991). An extensive description of the procedure with the relevant pseudocode is included in the paper. The procedure is tested in a stochastic optimisation-based decision support environment. Testing is done using a case study of a medium-sized family house. The result indicate promising performance. © 2024 Elsevier B.V. All rights reserved.
Citation - WoS: 2
Citation - Scopus: 4
A Computational Intelligence Decision-Support Environment for Architectural and Building Design: CIDEA
(IEEE, 2016) Ioannis Chatzikonstantinou; Chatzikonstantinou, Ioannis
Environmentally friendly and comfortable buildings are a much sought after goal in today's architectural practice. In order to improve energy consumption of buildings without sacrificing indoor comfort careful consideration of design decisions is needed. Simulation tools provide a solution to one aspect arising from this need namely the requirement for accurate quantitative results. On the other hand the complexity of the real-world design problems in question calls for decision support tools that integrate in addition to simulation optimization analysis and modeling. The aim of the paper is to present ongoing work on the development of such a tool. The focus of the tool is on abstraction of the technical complexity while maintaining a sufficient level of flexibility. The tool is designed according to an integrated workflow beginning from sampling data analysis model creation and testing up until the final analysis of the optimization results. We present the architecture of the platform as well as its application in two case studies one focusing on the design of an office tower and one on the design of a sustainable facade. Results from qualitative usage cases indicate favorable performance in supporting decision-making.
Citation - WoS: 14
Citation - Scopus: 18
A Multi-Objective Harmony Search Algorithm for Sustainable Design of Floating Settlements
(MDPI AG, 2016) Cemre Cubukcuoglu; Ioannis Chatzikonstantinou; Mehmet Fatih Tasgetiren; I. Sevil Sariyildiz; Quan-Ke Pan; Chatzikonstantinou, Ioannis; Tasgetiren, Mehmet Fatih; Sariyildiz, I. Sevil; Cubukcuoglu, Cemre; Pan, Quan-Ke
This paper is concerned with the application of computational intelligence techniques to the conceptual design and development of a large-scale floating settlement. The settlement in question is a design for the area of Urla which is a rural touristic region located on the west coast of Turkey near the metropolis of Izmir. The problem at hand includes both engineering and architectural aspects that need to be addressed in a comprehensive manner. We thus adapt the view as a multi-objective constrained real-parameter optimization problem. Specifically we consider three objectives which are conflicting. The first one aims at maximizing accessibility of urban functions such as housing and public spaces as well as special functions such as a marina for yachts and a yacht club. The second one aims at ensuring the wind protection of the general areas of the settlement by adequately placing them in between neighboring land masses. The third one aims at maximizing visibility of the settlement from external observation points so as to maximize the exposure of the settlement. To address this complex multi-objective optimization problem and identify lucrative alternative design solutions a multi-objective harmony search algorithm (MOHS) is developed and applied in this paper. When compared to the Differential Evolution algorithm developed for the problem in the literature we demonstrate that MOHS achieves competitive or slightly better performance in terms of hyper volume calculation and gives promising results when the Pareto front approximation is examined.
Citation - WoS: 11
Citation - Scopus: 12
A multi-objective self-adaptive differential evolution algorithm for conceptual high-rise building design
(Institute of Electrical and Electronics Engineers Inc., 2016) Berk Ekici; Ioannis Chatzikonstantinou; I. Sevil Sariyildiz; M. Fatih Tasgetiren; Quanke Pan; Ekici, Berk; Sariyildiz, Sevil; Chatzikonstantinou, Ioannis; Tasgetiren, M. Fatih; Pan, Quan-Ke
This paper presents a multi-objective self-adaptive differential evolution algorithm to solve the form-finding problem of high-rise building design in the conceptual phase. The aim of the research is to reach suitable high-rise design alternatives for hard and soft objectives which are construction cost per square meter structural displacement and visual perception of the spaces from the inside out subject to several constraints that are related with both high-rise construction regulations and profitability of the spaces. We formulate the problem as a multi-objective realparameter constrained optimization problem for three objectives that are inherently conflicting. To tackle this problem we developed two different optimization algorithms namely a Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and a Self-Adaptive Differential Evolution Algorithm (jDE) in order to obtain Pareto fronts with diversified non-dominated solutions. The extensive computational results show that the jDE algorithm yields much more desirable Pareto front than the NSGA-II algorithm. © 2017 Elsevier B.V. All rights reserved.
Citation - Scopus: 21
Addressing design preferences via auto-associative connectionist models: Application in sustainable architectural Façade design
(Elsevier B.V., 2017) Ioannis Chatzikonstantinou; I. Sevil Sariyildiz; Chatzikonstantinou, Ioannis; Sariyildiz, I. Sevil
Truly successful designs are characterized by both satisfaction of design goals and the presence of desirable physical features. Experienced design professionals are able to exercise their cognition to satisfy both aspects to a high degree. However complex design tasks represent challenges for human cognition and as such computational decision support systems emerge as a relevant topic. We present a computational decision support framework for treating preferences related to physical design features. The proposed framework is based on auto-associative machine learning models that inductively learn relationships between design features characterizing highly performing designs. The knowledge matter to be learned is derived through multi-objective stochastic optimization. The resulting auto-associative models are excited with a preference vector containing a favorable composition of design features. The models are able to alleviate those relationships that result in shortcomings of performance. The model thus outputs well performing design solution where preferences pertaining to physical features are also satisfied to the extent possible. The paper focuses on the applicability of the proposed approach in architectural design as an exceptional example of complex design discusses methods to evaluate model performance and validates the proposed method through an application focusing on the design of a sustainable façade. © 2017 Elsevier B.V. All rights reserved.
Citation - WoS: 30
Citation - Scopus: 42
Approximation of simulation-derived visual comfort indicators in office spaces: a comparative study in machine learning
(TAYLOR & FRANCIS LTD, 2016) Ioannis Chatzikonstantinou; Sevil Sariyildiz; Sariyildiz, Sevil; Chatzikonstantinou, Ioannis
In performance-oriented architectural design the use of advanced computational simulation tools may provide valuable insight during design. However the use of such tools is often a bottleneck in the design process given that computational requirements are usually high. This is a fact that mostly affects the early conceptual stage of design where crucial decisions mainly occur and available time is limited. In order to deal with this decision-makers frequently resort to drawing conclusions from experience and as such valuable insight that advanced computational methods have to offer is lost. This paper explores an alternative approach which builds on machine-learning algorithms that inductively learn from simulation-derived data yielding models that approximate to a good degree and are orders of magnitude faster. We focus on visual comfort of office spaces. This is a type of space that specifically requires visual comfort more than others. Three machine-learning methods are compared with respect to applicability in approximating daylight autonomy and daylight glare probability. The comparison focuses on accuracy and time cost of training and estimation. Results demonstrate that machine-learning-based approaches achieve a favourable trade-off between accuracy and computational cost and provide a worthwhile alternative for performance evaluations during architectural conceptual design.
Citation - WoS: 6
Citation - Scopus: 7
Conceptual Airport Terminal Design using Evolutionary Computation
(IEEE, 2015) Ioannis Chatzikonstantinou; Sevil Sariyildiz; Michael S. Bittermann; Sariyildiz, Sevil; Chatzikonstantinou, Ioannis; Bittermann, Michael S.
Passenger terminals are very complex buildings not only in their function form and structure but also in infrastructure security comfort energy which deal with huge investments both in terms of capital as well as in terms of resources and environmental impact. As such it is expected that they are designed to fulfill their purpose while minimizing their negative aspects to the environment. Identifying design solutions that satisfy these goals is a challenging task due to the complexity involved. The design task is characterized by excessive number of solutions conflicting goals and complex relations between design decision variables objectives and constraints. As such appropriate informed decisions that integrate as many design aspects as possible should be ensured as early as the conceptual stage of the design. In this study the problem of conceptual airport terminal design is addressed by means of computational decision support methodologies. The proposed method is based on the integration of the following components: i. a parametric modeling approach for enabling the instantaneous generation of a wide variety of designs ii. a multi-faceted evaluation scheme which integrates functional energy and architectural aspects iii. a Multi-Objective Genetic Algorithm namely the NSGA-II to identify well performing solutions. A computational model implementing the method is outlined and validation of the method is performed based on two different scenarios corresponding to commonly occurring airport configurations. The performance of two optimization runs with different population sizes as well as qualitative aspects of the resulting solutions is discussed.
Citation - WoS: 9
Citation - Scopus: 13
Designing Self-Sufficient Floating Neighborhoods Using Computational Decision Support
(IEEE, 2015) Ayca Kirimtat; Ioannis Chatzikonstantinou; Sevil Sariyildiz; Ayca Tartar; Sariyildiz, Sevil; Tartar, Ayca; Chatzikonstantinou, Ioannis; Kirimtat, Ayca
Floating settlements which introduce further design complexities over traditional developments have become an alternative for urban development due to climate change and shortage of land. This study aims to develop a floating settlement concept that presents an approach to the design of floating neighborhoods using parametric modelling techniques in combination with Intelligent Decision Support tools and optimization methods. Optimization results of two algorithms namely NSGA-II and DE are compared regarding to objectives. The objectives considered in this study are walkability within the neighborhoods scenic view and cost-effectiveness. Results suggest that DE performs better than NSGA-II in this problem. An application of the method is presented focusing on the design of floating neighborhoods in the project area namely Urla which is a seaside place along the coastline of Izmir Turkey.
Engineering Performance Simulations in Architectural Design Conception Atrium in Shenyang: a case study on thermal mass
(Education and research in Computer Aided Architectural Design in Europe, 2013) Michela Turrin; Ioannis Chatzikonstantinou; Martin J. Tenpierik; I. Sevil Sariyildiz; Turrin, Michela; Sariyildiz, Sevil; Chatzikonstantinou, Ioannis; Tenpierik, Martin; R. Stouffs , S. Sariyildiz
The paper tackles the integration of engineering performance simulations in the conceptual phase of architectural design with specific focus on parametric design processes. A general framework is exemplified in which the use of performance simulations and the learning process of the designer are discussed in relation to the parameterization process. A specific case study is presented more in details regarding the design of an atrium for the reuse of an existing building in Shenyang-China. Performance simulations concerning the thermal comfort in the atrium are presented and discussed in relation to the general framework. © 2022 Elsevier B.V. All rights reserved.
Citation - WoS: 4
Citation - Scopus: 7
Evolutionary Computation for Architectural Design of Restaurant Layouts
(IEEE, 2015) Cemre Ugurlu; Ioannis Chatzikonstantinou; Sevil Sariyildiz; M. Fatih Tasgetiren; Sariyildiz, Sevil; Chatzikonstantinou, Ioannis; Tasgetiren, M. Fatih; Ugurlu, Cemre
This paper presents the results obtained by NSGA-II and DE on a restaurant layout optimization problem trying to maximize total profit while minimizing investment. The problem entails the configuration of restaurant functions the decisions regarding the restaurant shell composition (fraction and position of windows dimensions) and how to shape and place the kitchen and service areas. The NSGA-II and DE algorithms are implemented in a Parametric Design Environment that is familiar in the architectural practice. We demonstrate that the DE algorithm achieves slightly better performance in terms of hypervolume calculation and achieve promising results when the Pareto front approximation is examined. To the best of our knowledge this is the first application of multi-objective approach for restaurant design.
Citation - WoS: 5
Citation - Scopus: 7
Identification of Sustainable Designs for Floating Settlements Using Computational Design Techniques
(IEEE, 2015) Cemre Ugurlu; Ioannis Chatzikonstantinou; Sevil Sariyildiz; Mehmet Fatih Tasgetiren; Sariyildiz, Sevil; Chatzikonstantinou, Ioannis; Tasgetiren, M. Fatih; Ugurlu, Cemre
This paper focuses on the conceptual design and the development of a floating neighborhood by taking advantage of computational methods. An application to a concept design of a floating neighborhood in the region of Urla - a coastal town close to Izmir in Turkey has been studied. The scenario that has been addressed concerns the development of an efficient floating settlement between four islands that are local to the study region. The whole study revolves around two issues first one is about configuration of the functions (accommodation marine yacht club public area) in order to maximize accessibility wind protection and visibility subject to both technical and nontechnical constraints. Second issue is to find a suitable form generated by shortest walk algorithm that decides how to create roads between functions where their places are gathered from optimization solutions. For the configuration of the functions since wind protection and visibility objectives as well as accessibility and visibility are conflicting with each other we make use of multi-objective evolutionary algorithms. The NSGA-II and DE algorithms are implemented in a Parametric Design Environment that is familiar in the architectural practice. We demonstrate that the NSGA-II performs slightly better in terms of hyper volume calculation and achieves promising results when the Pareto front approximation is examined.
Citation - WoS: 3
Citation - Scopus: 3
Interior Spatial Layout with Soft Objectives using Evolutionary Computation
(IEEE, 2016) Ioannis Chatzikonstantinou; Ebru Bengisu; Chatzikonstantinou, Ioannis; Bengisu, Ebru
This paper presents the design problem of furniture arrangement in a residential interior living space and addresses it by means of evolutionary computation. Interior arrangement is an important and interesting problem that occurs commonly when designing living spaces. It entails determining the locations of interior elements such as tables seating elements projection screens etc. in order to satisfy objectives. Despite it's commonality it is a challenging problem that entails mainly soft objectives related to perception and ergonomics as well as challenging constraints. This paper is an attempt to address this problem by means of Evolutionary Computation. We discuss the problem formulation focusing on perceptual aspects of the various elements of space. In particular we formulate a three objective problem with the following objectives: Maximization of visual perception of openings to the outside maximization of inter-person visual perception from the seating places and maximization of the openness of space. We provide results from a comparison of two MOEAs namely NSGA-II and HypE.
Citation - WoS: 13
Citation - Scopus: 16
Multi-objective diagrid facąde optimization using differential evolution
(Institute of Electrical and Electronics Engineers Inc., 2015) Ioannis Chatzikonstantinou; Berk Ekici; I. Sevil Sariyildiz; Basak Kundakci Koyunbaba; Ekici, Berk; Chatzikonstantinou, Ioannis; Sariyildiz, I. Sevil; Koyunbaba, Basak Kundakci
Facądes constitute one of the fundamental systems of contemporary buildings. They serve multiple purposes such as to ensure proper indoor climate to provide sufficient daylight but also to create a desirable architectural image. Integration of these aspects makes facąde design a complex task that requires significant effort in order to achieve well-performing results. It is thus desirable that systematic approaches to facąde design are developed. In this study we consider facąde design as a multiobjective optimization problem integrating diverse design criteria namely indoor daylight distribution structural performance and cost. We evaluate design performance by making use of simulation. Consequently we use Differential Evolution (DE) to search for best-tradeoff solutions. We compare the performance of two DE variants using the Hypervolume metric and also through qualitative inspection. We report facąde designs that demonstrate interesting and often unexpected features concluding that the proposed approach may lead to a novel more integrated design process. © 2017 Elsevier B.V. All rights reserved.
Citation - WoS: 8
Citation - Scopus: 14
Multi-Objective Optimization For Shading Devices in Buildings By Using Evolutionary Algorithms
(IEEE, 2016) Ayca Kirimtat; Basak Kundakci Koyunbaba; Ioannis Chatzikonstantinou; Sevil Sariyildiz; Ponnuthurai Nagaratnam Suganthan; Sariyildiz, Sevil; Chatzikonstantinou, Ioannis; Suganthan, Ponnuthurai Nagaratnam; Koyunbaba, Basak Kundakci; Kirimtat, Ayca
The reduction of energy consumption is a major challenge around the world. Architectural aspects have a significant place to minimize energy consumption to the maximum level. The use of large glazed facades causes overheating problems in certain climatic regions. Shading elements must be considered at an early stage in the design process to overcome this problem. An application of the method is presented focusing on the horizontal louvers integrated to a building in Izmir Turkey. The contributions of the paper can be summarized as follows. We show that most architectural design problems are basically real-parameter multi-objective constrained optimization problems. So any type of evolutionary and swarm optimization methods can be used in this field. A multi-objective self-adaptive differential evolution algorithm (jDEMO) inspired from the DEMO algorithm from the literature with some modifications is developed and compared to the well-known fast and nondominated sorting genetic algorithm so called NSGA-II in order to solve this complex problem and identify alternative design solutions to decision makers. Through the experimental results we show that the proposed algorithm generated slightly better results when comparing to the NSGA-II algorithm.
Citation - WoS: 7
Citation - Scopus: 9
Multi-Objective Optimization Through Differential Evolution for Restaurant Design
(IEEE, 2016) Cemre Cubukcuoglu; Ioannis Chatzikonstantinou; Berk Ekici; Sevil Sariyildiz; M. Fatih Tasgetiren; Ekici, Berk; Sariyildiz, Sevil; Chatzikonstantinou, Ioannis; Tasgetiren, M. Fatih; Cubukcuoglu, Cemre
This paper presents the results obtained by NSGA-II and jDEMO on a restaurant design optimization in the conceptual phase. A multi-objective problem is formulated by considering the minimization of investment and the maximization of customer count and maximization of visual perception subject to several constraints. The main problem requires the configuration of restaurant spaces with different seating groups decisions regarding the customer capacity fraction and position of the windows. The contributions of the paper can be summarized as follows. We show that most architectural design problems are basically real-parameter multi-objective constrained optimization problems. So any type of evolutionary and swarm optimization methods can be used in this field. A multi-objective self-adaptive differential evolution algorithm (jDEMO) inspired from the DEMO algorithm from the literature with some modifications is developed and compared to the well-known fast and non-dominated sorting genetic algorithm so called NSGA-II in order to solve this complex problem and identify alternative design solutions to decision makers. Through the experimental results we show that the proposed algorithm is competitive with the NSGA-II algorithm.
Citation - WoS: 9
Citation - Scopus: 10
Multi-Objective skylight optimization for a healthcare facility foyer space
(Institute of Electrical and Electronics Engineers Inc., 2017) Muhittin Yufka; Berk Ekici; Cemre Cubukcuoglu; Ioannis Chatzikonstantinou; I. Sevil Sariyildiz; Ekici, Berk; Chatzikonstantinou, Ioannis; Sariyildiz, I. Sevil; Yufka, Muhittin; Cubukcuoglu, Cemre
In this paper the design of a specific case study of a foyer space is concerned in healthcare facility. The design task of a healthcare facility in architectural perspective is one of the most challenging tasks in the architectural design field since it involves different spaces that have unique requirements. Specifically a foyer space has been considered as a gathering area that answers people's needs and expectations. The study shows an application of computational intelligence for a skylight design in foyer space. For this reason objective functions are considered to minimize skylight cost and to maximize the daylight performance of the interior space. Multi-Objective Self-Adaptive Ensemble Differential Evolution Algorithm and Non-Dominated Sorting Genetic Algorithm-II are proposed to tackle this complex problem. According to results jE-DEMO algorithm presents satisfactory solutions as well as NSGA-II. © 2017 Elsevier B.V. All rights reserved.
Citation - WoS: 7
Optimisation of energy consumption and daylighting using building performance surrogate model
(UNIV MELBOURNE, 2015) Elif Esra Aydin; Onur Dursun; Ioannis Chatzikonstantinou; Berk Ekici; Ekici, Berk; Chatzikonstantinou, Ioannis; Aydin, Elif Esra; Dursun, Onur; RH Crawford; A Stephan
Today the architects are expected to identify solutions that provide best trade-offs among an excessively large number of possible design alternatives. Within this context computational intelligence techniques prove to be valuable decision support tools. In parallel to this agenda the current study aimed to present a novel approach towards identifying non-dominated design solutions that minimize annual building energy consumption and improve indoor daylight conditions. We applied the method to an L plan shaped office design. In this hypothetical building design parameters of footprint area number of levels fenestration shading U-Values of building elements and HVAC system selection were set as variables, whereas total floor area and floor height were kept as constants in order to facilitate further practical relevance. A total of 105 simulations were performed for various values of the parameters. The resulting dataset was used to obtain two approximation models for each of the objective functions. A Multi-Objective Evolutionary Algorithm was subsequently used to obtain the set of non-dominated solutions for the problem. Our results indicated the applicability of the proposed approach for decision-making practices at the conceptual design phase of relevant cases.
pCOLAD: online sharing of parameters for collaborative architectural design
(Education and research in Computer Aided Architectural Design in Europe, 2014) Hans J.C. Hubers; Michela Turrin; Irem Erbas; Ioannis Chatzikonstantinou; Turrin, Michela; Erbas, Irem; Chatzikonstantinou, Ioannis; Hubers, Hans J. C.; E.M. Thompson
Simultaneous interdisciplinary architectural design from the very start of a project faces challenges in properly sharing information across disciplines. This research developed a method and related digital tool to improve collaborative design and aimed at making selected information to be shared faster and more transparently. The method consists of developing alternative parametric solutions for different parts of the design in such a way that crucial parameters form a link between these parts. The digital tool has been developed for Grasshopper and permits synchronic (real-time over the Internet) and a-synchronic sharing of these parameters. The design alternatives are evaluated with specific criteria pros and cons in an Internet Forum and discussed via a video-conferencing tool. Decisions are then taken in a collaborative manner through voting. The paper describes the method based on a case study. © 2024 Elsevier B.V. All rights reserved.
Citation - WoS: 258
Citation - Scopus: 318
Review of simulation modeling for shading devices in buildings
(PERGAMON-ELSEVIER SCIENCE LTD, 2016) Ayca Kirimtat; Basak Kundakci Koyunbaba; Ioannis Chatzikonstantinou; Sevil Sariyildiz; Sariyildiz, Sevil; Chatzikonstantinou, Ioannis; Koyunbaba, Basak Kundakci; Kirimtat, Ayca
Many countries around the world are confronted with the challenge of decreasing energy consumption while the use of electrical appliances is continuously increasing in buildings. The requirement to minimize the energy consumption can be fulfilled by revaluating architectural aspects. One of these aspects is related to overheating problems caused by facades with large glazed portions. In such designs shading elements must carefully be integrated and considered at an early-design stage in the design process. Shading of buildings is crucial especially in climates with hot summer. It is significant to protect the window from solar radiation in summer while allowing maximum solar radiation in winter. For this reason precise figures of their performance are needed. As such simulation tools are often used for identifying the most suitable shading element that suits the building. In literature there are many studies that have been done to designate the energy performance of shading devices in buildings by using simulation tools. This study focuses both on the shading device types used in the building sector and the previous studies done for designating the performance aspects of different shading devices types. Numerous studies for different building types located in different climatic regions have been reviewed in order to underline the importance of simulation modeling for shading devices in buildings. (C) 2015 Elsevier Ltd. All rights reserved.