COURSE UNIT TITLE

: DECISION MANAGEMENT AND OPTIMIZATION IN ARCHITECTURE

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
ARC 5209 DECISION MANAGEMENT AND OPTIMIZATION IN ARCHITECTURE ELECTIVE 2 2 0 6

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

ASSISTANT PROFESSOR ASLIHAN ŞENEL SOLMAZ

Offered to

Structural Construction Design
Structural Construction Design

Course Objective

The course aims to provide students with knowledge on the application of decision management and optimization methods in architecture. This course aims to address optimal decision-making processes in architecture in a multi-layered manner at the theoretical, methodological, and practical levels. The course first focuses on decision theory, behavioral decision theories, multi-criteria decision-making (MCDM) methods, and decision modeling approaches used in solving decision problems. Subsequently, optimization methods, which enable the numerical, objective, and performance-oriented solution of decision processes, are examined from a critical perspective in the context of architecture. In multidimensional decision areas in architecture, such as energy efficiency, daylight optimization, material performance, construction and life cycle costs, the course emphasizes linear/nonlinear optimization, heuristic algorithms, multi-objective optimization techniques, and the integration of these techniques with simulation and modeling tools. The main objective of the course is to enable students to systematically analyze complex decision systems with theoretical depth, integrate qualitative and quantitative methods into the decision process, and develop multi-criteria, computational, and strategic approaches to decision problems.

Learning Outcomes of the Course Unit

1   To understand decision management and developing optimal decision-making skills in architecture
2   To understand the basic concepts of optimization and gaining knowledge about their applications in architecture
3   To understand and classify optimization problems that arise at different stages in the building life cycle process
4   To obtain information about the basic steps in the application of optimization methods in decision-making processes and the integration of the programs used during design process.
5   Ability to understand, interpret and discuss numerical data obtained as a result of optimization application

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to the course, stating its purpose and scope, providing information about research assignments and applications.
2 Explanation of basic concepts: Decision management and optimization; the importance of decision management and optimization in optimal decision-making processes in architecture.
3 Decision theory, decision-making under uncertainty and risk, decision-making approaches. Application
4 Decision theory, decision making under uncertainty and risk, decision making approaches. Application
5 Multi-criteria decision making methods. Application
6 Multi-criteria decision making methods. Application
7 Discussion and evaluation of research assignments and applications.
8 Submission of research assignments and applications. Discussion and evaluation.
9 Optimization applications in architecture: classification of optimization problems from a building life cycle perspective; single-objective and multi-objective optimization problems; optimization methods and approaches used.
10 Optimization problems related to building energy and environmental performance, their classification (single-objective and multi-objective problems), and proposed solutions. Application
11 Simulation-based optimization application. Application
12 Single-objective optimization problem and application (using programs such as EnergyPlus and GenOpt). Application
13 Multi-objective optimization problem and application (using programs such as EnergyPlus and GenOpt). Application
14 Discussion and evaluation regarding the final research assignment and applications.
15 Discussion and evaluation regarding the final research assignment and applications.

Recomended or Required Reading

Halıcıoğlu, F. H. 2005. Kalite fonksiyon yayılımı yönteminin mimarlıkta uygulanmasına yönelik model önerisi ve bir bina projesi kapsamında irdelenmesi. Doktora Tezi, Dokuz Eylül Üniversitesi, Fen Bilimleri Enstitüsü, Izmir, Türkiye.
Jato-Espino, D., Castillo-Lopez, E., Rodriguez-Hernandez, J., & Canteras-Jordana, J. C. 2014. A review of application of multi-criteria decision making methods in construction. Automation in construction, 45, 151-162.
Parmigiani, G., & Inoue, L. 2009. Decision theory: Principles and approaches. John Wiley & Sons.
Saaty, T. L. 1990. How to make a decision: the analytic hierarchy process. European journal of operational research, 48(1), 9-26.
Triantaphyllou, E. 2000. Multi-criteria decision making methods. In Multi-criteria decision making methods: A comparative study (pp. 5-21). Springer, Boston, MA.
Senel Solmaz, A. 2015. A decision support model based on simulation and multi-objective optimization to determine optimum solutions for building energy performance. PhD. Thesis, Dokuz Eylul University, Izmir, Turkey.
Senel Solmaz, A., Halicioglu, F.H., Gunhan, S.: An Approach for Making Optimal Decisions in Building Energy Efficiency Retrofit Projects, Indoor and Built Environment, 27(2018), pp. 348-368, ttps:/doi.org/10.1177/1420326X16674764
Asadi, E., Da Silva, M. G., Antunes, C. H. ve Dias, L. S. (2013). State of the art on retrofit strategies selection using multi-objective optimization and genetic algorithms. F. Pacheco Torgal, M. Mistretta, A. R. Kaklauskas, C. G. Granqvist ve L. F. Cabeza (Ed.), Nearly Zero Energy Building Refurbishment (279-297). London: Springer.
Asadi, E., Da Silva, M. G., Antunes, C. H., Dias, L. S. ve Glicksman, L. (2014). Multi-objective optimization for building retrofit: A model using genetic algorithm and artificial neural network and an application. Energy and Buildings, 81(0), 444-456.

Planned Learning Activities and Teaching Methods

Lectures, practice, project, individual research, presentation of the assignments, project submission.
The stages of the project that each student will do individually will be critiqued and improved during the course practice hours.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 ASG ASSIGNMENT/PRESENTATION
2 FIN FINAL EXAM
3 FCG FINAL COURSE GRADE ASG * 0.40 +FIN * 0.60
4 RST RESIT
5 FCGR FINAL COURSE GRADE (RESIT) ASG * 0.40 +RST * 0.60


Further Notes About Assessment Methods


Assessment Criteria

Homework %10 (LO1, LO2, LO3, LO4, LO5)
Project Submission %50 (LO1, LO2, LO3, LO4, LO5)
Final Exam %40 (LO1, LO2, LO3, LO4, LO5)

Language of Instruction

Turkish

Course Policies and Rules

-

Contact Details for the Lecturer(s)

PROF. FAHRIYE HILAL HALICIOĞLU hilal.halicioglu@deu.edu.tr
ASSIST. PROF. ASLIHAN ŞENEL SOLMAZ aslihan.senel@deu.edu.tr

Office Hours

To be announced

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 4 2 8
Tutorials 11 2 22
Preparations before/after weekly lectures 12 4 48
Preparation for final exam 1 10 10
Preparing assignments 1 7 7
Preparing presentations 4 8 32
Project Preparation 1 25 25
Final 1 2 2
TOTAL WORKLOAD (hours) 154

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.1534
LO.2534
LO.3534
LO.4534
LO.5534

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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