COURSE UNIT TITLE

: MATHEMATICAL MODELS IN PLANNING

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
PLN 2256 MATHEMATICAL MODELS 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

In this course, mathematical models used in planning will be introduced. For each model to be covered, the theoretical framework will first be explained, followed by the numerical solution of at least one planning problem using the described model as an example. By the end of the course, students will have the necessary knowledge about which model to use and when, as well as the type of data required for using the model. Real data collection is excluded from the course scope, and examples will be solved using prepared data.

Learning Outcomes of the Course Unit

1   1. Understand the formulations and algorithms of the basic and classical mathematical models in planning,
2   2. Comprehend the areas of application pertaining to each mathematical model,
3   3. Differentiate the objectives and requirements pertaining to to different mathematical models in planning,
4   4. Analyze the outcomes of the basic mathematical models in city planning,
5   5. Decide which mathematical model to use under given assumptions and problem definitions.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Economic-base Model: Base Multiplier and Dependency Ratio
2 Economic-base Model: Location Quotient Technique
3 Economic-base Model: Minimum Requirements Methot
4 Constant Share/Shift Share Method
5 Constant Share/Shift Share Method
6 Introduction to Gravity Model
7 Mid-term Exam
8 Single Constraint Location Model for Retail
9 Single Constraint Location Model for Retail
10 Hansen Model
11 Hansen Model
12 Lowry-Garin Model
13 Lowry-Garin Model
14 Transportation Models
15 Transportation Models

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