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 2254 MATHEMATICAL MODELS IN PLANNING COMPULSORY 2 0 0 3

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 mathemathical models in city planning. For each subject, the theretical backgroung 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 model to choose under different circumstances. The students will also be aware of the data requirements for each model. Data collection and data manupulation is beyond the scope of this course.

Learning Outcomes of the Course Unit

1   Understand the formulations and algorithms of the basic and classical mathemathical models in planning,
2   Comprehend the areas of application pertaining to each mathemathical model,
3   Differentiate the objevtives and requirements pertaining to to different mathemathical models in planning,
4   Analyse the outcomes of the basic mathemathical models in city planning,
5   Decide which mathemathical 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 Hansen Model
10 Lowry-Garin Model
11 Lowry-Garin Model
12 Transportation Models
13 Double Constraint Model for Trip Distribution
14 Double Constraint Model for Trip Distribution
15 Final Examinations Week
16 Final Examinations Week

Recomended or Required Reading

Çubukçu, K.M. (2008) Planlamada Klasik Sayısal Yöntemler, ÖDTÜ 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


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Midterm and final examinations.

Language of Instruction

Turkish

Course Policies and Rules

1. Attendance is required.
2. Plagiarism and all other means of cheating are strictly prohibited.

Contact Details for the Lecturer(s)

Dokuz Eylul University, Tinaztepe Campus
School of Architecture
Department of City and Regional Planning
Room #109
Buca/IZMIR 35160
TURKEY
mert.cubukcu@deu.edu.tr
http://kisi.deu.edu.tr/mert.cubukcu

Office Hours

Wednesdays, 8:30-10:30

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 13 2 26
Preparation before/after weekly lectures 13 2 26
Preparation for Mid-term Examination 1 10 10
Preparation for Final Examination 1 15 15
Final Examination 1 2 2
Mid-Term Examination 1 2 2
TOTAL WORKLOAD (hours) 81

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.111
LO.211
LO.311
LO.411
LO.511