Browsing by Author "Cubukcuoglu, Cemre"

Now showing 1 - 13 of 13

Citation - WoS: 15
Citation - Scopus: 22
A discrete event simulation procedure for validating programs of requirements: The case of hospital space planning
(ELSEVIER, 2020) Cemre Cubukcuoglu; Pirouz Nourian; I. Sevil Sariyildiz; M. Fatih Tasgetiren; Nourian, Pirouz; Tasgetiren, M. Fatih; Sariyildiz, I. Sevil; Cubukcuoglu, Cemre
This paper introduces a Discrete-Event Simulation (DES) tool developed as a parametric CAD program for validating a program of requirements (PoR) for hospital space planning. The DES model simulates the procedures of processing of patients treated by doctors calculating patient throughput and patient waiting times based on the number of doctors patient arrivals and treatment times. In addition the tool is capable of defining space requirements by taking hospital design standards into account. Using this tool what-if scenarios and assumptions on the PoR about space planning can be tested and/or validated. The tool is ultimately meant for reducing patient waiting times and/or increasing patient throughput by checking the match of the layout of a hospital with respect to its procedural operations. This tool is envisaged to grow into a toolkit providing a methodological framework for bringing Operations Research into Architectural Space Planning. The tool is implemented in Python for Grasshopper (GH) a plugin of Rhinoceros CAD software using the SimPy library. (C) 2020 The Authors. Published by Elsevier B.V.
Citation - WoS: 5
Citation - Scopus: 7
A Memetic Algorithm for the Bi-Objective Quadratic Assignment Problem
(ELSEVIER SCIENCE BV, 2019) Cemre Cubukcuoglu; M. Fatih Tasgetiren; I. Sevil Sariyildiz; Liang Gao; Murat Kucukvar; Tasgetiren, M. Fatih; Kucukvar, Murat; Sariyildiz, I. Sevil; Fatih Tasgetiren, M.; Cubukcuoglu, Cemre; Sevil Sariyildiz, I.; Gao, Liang; CH Dagli; GA Suer
Recently multi-objective evolutionary algorithms (MOEAs) have been extensively used to solve multi-objective optimization problems (MOPs) since they have the ability to approximate a set of non-dominated solutions in reasonable CPU times. In this paper we consider the bi-objective quadratic assignment problem (bQAP) which is a variant of the classical QAP which has been extensively investigated to solve several real-life problems. The bQAP can be defined as having many input flows with the same distances between the facilities causing multiple cost functions that must be optimized simultaneously. In this study we propose a memetic algorithm with effective local search and mutation operators to solve the bQAP. Local search is based on swap neighborhood structure whereas the mutation operator is based on ruin and recreate procedure. The experimental results show that our bi-objective memetic algorithm (BOMA) substantially outperforms all the island-based variants of the PASMOQAP algorithm proposed very recently in the literature. (C) 2019 The Authors. Published by Elsevier Ltd.
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 - Scopus: 16
Design of rectangular façade modules through computational intelligence
(Institute of Electrical and Electronics Engineers Inc., 2017) Selim Karaman; Berk Ekici; Cemre Cubukcuoglu; Basak Kundakci Koyunbaba; Ilker Kahraman; Ekici, Berk; Karaman, Selim; Cubukcuoglu, Cemre; Koyunbaba, Basak Kundakci; Kahraman, Ilker
This paper presents an implementation of multiobjective optimization for a rectangular façade design proposal in a healthcare building's common space. Objectives are to maximize daylight performance and to minimize façade construction cost. The aim of this study is to enhance indoor comfort of an existing healthcare building by concerning cost-effective façade design alternatives subject to several constraints. To handle the problem we formulate a multi-objective real-parameter constraint problem. In order to solve this Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and Multi-objective Self-Adaptive Ensemble Differential Evolution (jE-DEMO) algorithms are used. Finally both algorithms are capable to discover desirable set of design alternatives. © 2017 Elsevier B.V. All rights reserved.
Citation - WoS: 9
Design of Rectangular Facade Modules through Computational Intelligence Case of Common Space in Healthcare Building
(IEEE, 2017) Selim Karaman; Berk Ekici; Cemre Cubukcuoglu; Basak Kundakci Koyunbaba; Ilker Kahraman; Ekici, Berk; Karaman, Selim; Cubukcuoglu, Cemre; Koyunbaba, Basak Kundakci; Kahraman, Ilker
This paper presents an implementation of multi-objective optimization for a rectangular facade design proposal in a healthcare building's common space. Objectives are to maximize daylight performance and to minimize facade construction cost. The aim of this study is to enhance indoor comfort of an existing healthcare building by concerning cost-effective facade design alternatives subject to several constraints. To handle the problem we formulate a multi-objective real-parameter constraint problem. In order to solve this Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and Multi-objective Self-Adaptive Ensemble Differential Evolution (jE_DEMO) algorithms are used. Finally both algorithms are capable to discover desirable set of design alternatives.
Citation - WoS: 29
Citation - Scopus: 38
Hospital 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, Cemre
Hospital 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.
Citation - WoS: 7
Citation - Scopus: 9
Indoor Environmental Quality Optimisation Model for Institutional Care Rooms of Elderly People
(MDPI, 2023) Cemre Cubukcuoglu; Arzu Cilasun Kunduraci; Sahar Asadollahi Asl Zarkhah; Zarkhah, Sahar Asadollahi Asl; Cubukcuoglu, Cemre; Cilasun Kunduraci, Arzu; Asadollahi Asl Zarkhah, Sahar; Kunduraci, Arzu Cilasun
It is known that the elderly usually spend the last years of their lives indoors with little contact with others and the outside environment. Indoor environmental quality (IEQ) conditions related to lighting air quality thermal comfort and acoustics directly affect their quality of life. In this study the main focus is on the design of institutional care rooms for elderly people to create an indoor comfort. However considering all four factors of IEQ in one model is a challenging task. A multi-objective problem is formulated based on a weighted sum of IEQ components in a parametric modelling environment using computational design methods. Several simulation tools are utilised and a Self-Adaptive Ensemble Differential Evolution Algorithm is proposed to tackle this complex problem. The results show that optimal ranges for each IEQ component are achieved with average values reaching 72% of the ideal benchmarks after the algorithm is converged. Results reveal strong correlations between IEQ components. This significant improvement in indoor environmental quality (IEQ) demonstrates the efficacy of the optimisation algorithm used. This study emphasises the flexibility and relevance of these findings for wider implementation in similar settings.
Citation - WoS: 2
Citation - Scopus: 4
Multi-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, Ayca
The 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.
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: 12
Citation - Scopus: 19
Optimal 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, Cemre
The 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.
Citation - WoS: 33
Citation - Scopus: 42
OPTIMUS: 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, Cemre
Most 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.
Citation - WoS: 99
Citation - Scopus: 115
Performative computational architecture using swarm and evolutionary optimisation: A review
(Elsevier Ltd, 2019) Berk Ekici; Cemre Cubukcuoglu; Michela Turrin; I. Sevil Sariyildiz; Ekici, Berk; Turrin, Michela; Sariyildiz, I. Sevil; Cubukcuoglu, Cemre
This study presents a systematic review and summary of performative computational architecture using swarm and evolutionary optimisation. The taxonomy for one hundred types of studies is presented herein that includes different sub-categories of performative computational architecture such as sustainability cost functionality and structure. Specifically energy daylight solar radiation environmental impact thermal comfort life-cycle cost initial and global costs energy use cost space allocation logistics structural assessment and holistic design approaches are investigated by considering their corresponding performance aspects. The main findings including optimisation and all the types of parameters are presented by focussing on different aspects of buildings. In addition usage of form-finding parameters of all reviewed studies and the distributions for each performance objectives are also presented. Moreover usage of swarm and evolutionary optimisation algorithms in reviewed studies is summarised. Trends in publications published years problem scales and building functions are examined. Finally future prospects are highlighted by focussing on different aspects of performative computational architecture in accordance to the evidence collected based on the review process. © 2018 Elsevier B.V. All rights reserved.