Çubukçuoğlu, Cemre
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Dr.Öğr.Üyesi
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01.01.10.01. İç Mimarlık ve Çevre Tasarımı Bölümü
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Sustainable Development Goals
1NO POVERTY
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2ZERO HUNGER
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3GOOD HEALTH AND WELL-BEING
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4QUALITY EDUCATION
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5GENDER EQUALITY
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6CLEAN WATER AND SANITATION
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7AFFORDABLE AND CLEAN ENERGY
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8DECENT WORK AND ECONOMIC GROWTH
1
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9INDUSTRY, INNOVATION AND INFRASTRUCTURE
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10REDUCED INEQUALITIES
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11SUSTAINABLE CITIES AND COMMUNITIES
2
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12RESPONSIBLE CONSUMPTION AND PRODUCTION
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13CLIMATE ACTION
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14LIFE BELOW WATER
1
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15LIFE ON LAND
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16PEACE, JUSTICE AND STRONG INSTITUTIONS
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17PARTNERSHIPS FOR THE GOALS
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16
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324
h-index
9
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15
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252
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16
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9
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WoS Citation Count
246
Scopus Citation Count
328
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WoS Citations per Publication
15.38
Scopus Citations per Publication
20.50
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9
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| Journal | Count |
|---|---|
| 2017 IEEE Congress on Evolutionary Computation CEC 2017 | 2 |
| IEEE Congress on Evolutionary Computation (CEC) | 2 |
| Algorithms | 2 |
| Automation in Construction | 1 |
| Building and Environment | 1 |
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16 results
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Conference Object Citation - WoS: 7Citation - Scopus: 9Multi-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, CemreThis 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.Conference Object Citation - WoS: 9Citation - Scopus: 10Multi-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, CemreIn 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.Article Citation - WoS: 5Citation - Scopus: 5Daylight Enhancement Strategies Through Roof for Heritage Buildings(Solarlits, 2024) Nurefsan Sönmez; Arzu Cilasun Kunduraci; Cemre Cubukcuoglu; Çubukçuoğlu, Cemre; Sönmez, Nurefşan; Kunduracı, Arzu CılasunEnhancing daylighting in heritage buildings is a complex challenge that requires a delicate balance between preserving architectural integrity and improving visual comfort. This paper investigates enhancing daylight in heritage buildings balancing preservation and visual comfort. It focuses on a 1905 heritage building undergoing reconstruction addressing insufficient daylight on the ground floor and glare on the first floor. The study investigated novel design solutions by using simulation and optimization approaches. A multiobjective optimization algorithm called JDEMO Algorithm (a multi-objective self-adaptive differential evolution algorithm) was utilized to obtain Pareto optimal results and integrated with performative simulations using ClimateStudio (CS) plug-in for Grasshopper. Strategies include altering skylight glazing materials surface materials and using Tubular Daylight Guidance Systems (TDGS). Results show TDGS with larger diameters improve Useful Daylight Illuminance (UDI) and reduce Spatial Disturbing Glare (sDG). Material selection impacts daylight distribution emphasizing the importance of skylight glazing materials. While specific to one case this research has wider implications for heritage preservation and daylighting. By innovating sustainable design it contributes to preserving heritage buildings while enhancing visual comfort. © 2024 Elsevier B.V. All rights reserved.Article Citation - WoS: 14Citation - Scopus: 18A 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-KeThis 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.Article Citation - WoS: 33Citation - Scopus: 42OPTIMUS: Self-Adaptive Differential Evolution with Ensemble of Mutation Strategies for Grasshopper Algorithmic Modeling(MDPI, 2019) Cemre Cubukcuoglu; Berk Ekici; Mehmet Fatih Tasgetiren; Sevil Sariyildiz; Ekici, Berk; Sariyildiz, Sevil; Tasgetiren, Mehmet Fatih; Cubukcuoglu, CemreMost of the architectural design problems are basically real-parameter optimization problems. So any type of evolutionary and swarm algorithms can be used in this field. However there is a little attention on using optimization methods within the computer aided design (CAD) programs. In this paper we present Optimus which is a new optimization tool for grasshopper algorithmic modeling in Rhinoceros CAD software. Optimus implements self-adaptive differential evolution algorithm with ensemble of mutation strategies (jEDE). We made an experiment using standard test problems in the literature and some of the test problems proposed in IEEE CEC 2005. We reported minimum maximum average standard deviations and number of function evaluations of five replications for each function. Experimental results on the benchmark suite showed that Optimus (jEDE) outperforms other optimization tools namely Galapagos (genetic algorithm) SilverEye (particle swarm optimization) and Opossum (RbfOpt) by finding better results for 19 out of 20 problems. For only one function Galapagos presented slightly better result than Optimus. Ultimately we presented an architectural design problem and compared the tools for testing Optimus in the design domain. We reported minimum maximum average and number of function evaluations of one replication for each tool. Galapagos and Silvereye presented infeasible results whereas Optimus and Opossum found feasible solutions. However Optimus discovered a much better fitness result than Opossum. As a conclusion we discuss advantages and limitations of Optimus in comparison to other tools. The target audience of this paper is frequent users of parametric design modelling e.g. architects engineers designers. The main contribution of this paper is summarized as follows. Optimus showed that near-optimal solutions of architectural design problems can be improved by testing different types of algorithms with respect to no-free lunch theorem. Moreover Optimus facilitates implementing different type of algorithms due to its modular system.Article Citation - WoS: 12Citation - Scopus: 19Optimal Design of new Hospitals: A Computational Workflow for Stacking- Zoning- and Routing(ELSEVIER, 2022) Cemre Cubukcuoglu; Pirouz Nourian; I. Sevil Sariyildiz; M. Fatih Tasgetiren; Nourian, Pirouz; Tasgetiren, M. Fatih; Sariyildiz, I. Sevil; Cubukcuoglu, CemreThe paper proposes a generative design workflow for three major hospital layout planning steps to satisfy multiplex configurational requirements. The initial step is stacking through clustering functional spaces into floor plans for which a spectral method is presented. Subsequently a novel simultaneous process of zoning and routing is proposed as a Mixed-Integer Programming problem-solving task, performed on a quadrilateral mesh whose faces and edges are allocated respectively to the rooms and the corridors. The paper situates the workflow in the context of an Activity-Relations-Chart for a general hospital while demonstrating explaining and justifying the generated optimal floor plans. The conversion of the hospital layout problem to a Mixed-Integer Programming problem enables the use of existing Operations Research solvers allowing for the generation of optimal solutions in a digital design environment. The comprehensive problem formulation for a real-world scenario opens a new avenue for utilization of mathematical programming/optimization in healthcare design.Conference Object Citation - WoS: 5Citation - Scopus: 7Identification 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, CemreThis 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.Conference Object Citation - WoS: 2Citation - Scopus: 4Multi-objective harmony search algorithm for layout design in theatre hall acoustics(Institute of Electrical and Electronics Engineers Inc., 2016) Cemre Cubukcuoglu; Ayca Kirimtat; M. Fatih Tasgetiren; Ponnuthurai Nagaratnam Suganthan; Quanke Pan; Tasgetiren, M. Faith; Suganthan, P. N.; Cubukcuoglu, Cemre; Pan, Quan-Ke; Kirimtat, AycaThe aim of the research is to find a feasible set of theatre hall design alternatives for two objectives which are the total cost and the reverberation time subject to several constraints. We formulate the problem as a multi-objective realparameter constrained optimization problem. To handle this problem we investigated two different optimization algorithms namely a Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and a multi-objective Harmony Search algorithm (MOHS) in order to gather Pareto front approximation with a set of non-dominated solutions. We demonstrate that the MOHS yields slightly better results than the NSGA-II algorithm. © 2017 Elsevier B.V. All rights reserved.Article HOPCA: Hospital Layout Design Optimization Using Computational Architecture(TU Delft, 2023) Çubukçuoğlu, CemreArticle Citation - WoS: 29Citation - Scopus: 38Hospital layout design renovation as a Quadratic Assignment Problem with geodesic distances(ELSEVIER, 2021) Cemre Cubukcuoglu; Pirouz Nourian; M. Fatih Tasgetiren; I. Sevil Sariyildiz; Shervin Azadi; Nourian, Pirouz; Azadi, Shervin; Tasgetiren, M. Fatih; Sariyildiz, I. Sevil; Cubukcuoglu, CemreHospital facilities are known as functionally complex buildings. There are usually configurational problems that lead to inefficient transportation processes for patients medical staff and/or logistics of materials. The Quadratic Assignment Problem (QAP) is a well-known problem in the field of Operations Research from the category of the facility's location/allocation problems. However it has rarely been utilized in architectural design practice. This paper presents a formulation of such logistics issues as a QAP for space planning processes aimed at renovation of existing hospitals a heuristic QAP solver developed in a CAD environment and its implementation as a computational design tool designed to be used by architects. The tool is implemented in C# for Grasshopper (GH) a plugin of Rhinoceros CAD software. This tool minimizes the internal transportation processes between interrelated facilities where each facility is assigned to a location in an existing building. In our model the problem of assignment is relaxed in that a single facility may be allowed to be allocated within multiple voxel locations thus alleviating the complexity of the unequal area assignment problem. The QAP formulation takes into account both the flows between facilities and distances between locations. The distance matrix is obtained from the spatial network of the building by using graph traversal techniques. The developed tool also calculates spatial geodesic distances (walkable easiest and/or shortest paths for pedestrians) inside the building. The QAP is solved by a heuristic optimization algorithm called Iterated Local Search. Using one exemplary real test case we demonstrate the potential of this method in the context of hospital layout design/re-design tasks in 3D. Finally we discuss the results and possible further developments concerning a generic computational space planning framework.
