COURSE UNIT TITLE

: QUANTITATIVE TECHNIQUES IN PLANNING

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
PLN 2251 QUANTITATIVE TECHNIQUES IN PLANNING COMPULSORY 2 0 0 2

Offered By

City and Regional Planning

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

PROFESSOR DOCTOR KEMAL MERT ÇUBUKÇU

Offered to

City and Regional Planning

Course Objective

The main objective of this course is to introduce the basic and classical quantitative techniques in city planning. For each subject, the theoretical background will be introduced first. Then, each subject will be discussed in detail through at least one numerically solved example. The students will be able to decide which technique to choose under different circumstances. The students will also be aware of the data requirements for each technique. Data collection and data manipulation is beyond the scope of this course.

Learning Outcomes of the Course Unit

1   1. Understand the formulations and algorithms of the basic and classical quantitative techniques in city planning
2   2. Comprehend the areas of application pertaining to each quantitative technique,
3   3. Differentiate the objevtives and requirements pertaining to different quantitative techniques in city planning
4   4. Analyse the outcomes of the basic quantitative techniques in city planning
5   5. Decide which quantitative technique to use under given assumptions and problem definitions
6   6. Grasp the basic concepts of network analysis and solve introductory level problems.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Architectural Programming
2 Static optimization and Linear Programming
3 Static optimization and Linear Programming
4 Static optimization and Linear Programming
5 Game Theory
6 Game Theory
7 Game Theory
8 Mid-term Exam
9 Decision Theory and Decisin Tree
10 Decision Theory and Decisin Tree
11 Cost-Benefit Analysis
12 Cost-Benefit Analysis
13 Cost-Benefit Analysis
14 Network Analysis - Shortest Path Algorithm
15 Network Analysis - Minimum Spanning Tree

Recomended or Required Reading

Çubukçu, K.M. (2015) Planlamada Klasik Sayısal Yöntemler, 4. Baskı. Nobel Yayınları
Lee, C. (1973) Models in Planning: An Introduction to the Use of Quantitative Models in Planning, Pergamon Press
Dökmeci, V.(2005) Planlamada Sayısal Yöntemler, ITÜ Yayınevi
Klosterman, R. E. (1990), Community Analysis and Planning Techniques, Savage, Md.: Rowman & Littlefield

Planned Learning Activities and Teaching Methods

Lectures, theoretical presentations and solved examples.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 FINS FINAL EXAM
3 FCG FINAL COURSE GRADE MTE * 0.50 + FINS * 0.50
4 RST RESIT
5 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.50 + RST * 0.50


Further Notes About Assessment Methods

None

Assessment Criteria

Assessment will be based on a Midterm Exam and a Final Exam.

Language of Instruction

Turkish

Course Policies and Rules

Any form of cheating will result in the initiation of disciplinary proceedings.

Contact Details for the Lecturer(s)

Dokuz Eylül Üniversitesi Tınaztepe Yerleşkesi
Mimarlık Fakültesi
Şehir ve Bölge Planlama Bölümü
Oda No: 109
Buca/IZMIR 35160

Office Hours

Mondays 1-2 hours

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 2 28
Preparations before/after weekly lectures 14 1 14
Preparation for midterm exam 1 8 8
Preparation for final exam 1 8 8
Final 1 1 1
Midterm 1 1 1
TOTAL WORKLOAD (hours) 60

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13PO.14PO.15PO.16PO.17
LO.134
LO.244
LO.345
LO.445
LO.545
LO.645