1. About the lecturer Dr. Qing Lu (Henry) – Grew up in Shanghai, China – Lived in Singapore from 1994 to 2014 – Came to IEU last September Contact information o Office: C-808, Tel: 448-8295 o e-mail: lu.qing@ieu.edu.trlu.qing@ieu.edu.tr o Course materials will be posted online every week Warning ahead No plagiarism (from other students or Internet) Keep classroom order Two-way communication vital, let me know whether you understand or not anything concerned

2. LOG 522: Quantitative Methods in Logistics Management Lecture 1: Introduction

3. Textbook 2 Operations Research: Applications and Algorithms / Wayne L. Winston. Cengage Learning; 4th edition, 2004.

4. What is Operations Research (OR)? OR/MS (management science): – a scientific approach to decision making that seeks to best design and operate a system, usually under conditions requiring the allocation of scarce resources (Winston 2004, p1) A system is an organization of interdependent components that work together to accomplish the goal of the system Scientific: using mathematical models Best: optimization Conditions: constraints

5. Why This Course? We will focus on logistics system OR is a tool for us to optimize the logistics system OR itself can be used in many fields, but we only study models related to logistics systems Only 5 chapters of the textbook will be studied in this course

6. Modeling Steps Formulate the Problem Observe the System Formulate a Mathematical Model of the Problem Verify the Model and Use the Model for Prediction Select a Suitable Alternative Present the Results and Conclusions of the Study Implement and Evaluate Recommendation

7. OR Model Components OR Model – Decision variables – Object functions – Constraints Purpose: find an optimal solution

8. OR Model Variances Static versus dynamic Linear versus nonlinear Integer versus non-integer Deterministic versus stochastic

9. Course Objectives and Overview Equip the students to  Understand basic mathematical modelling  Solve problems with optimization models (by hands and computers) Four sections in this course  Linear programming (Ch.3)  Integer linear programming (Ch.9)  Network models (Ch.7 & 8)  Decision making models (Ch. 13)

10. Course Evaluation 5% attendance – Attend lectures as many as you can 15% homework – Submit homework on time and understand them 40% mid exam at the middle of the course – Get familiar with the context during the lesson. Ask questions if you don’t understand. – It is too late for a student to contact lecturer after the exam! 40% final exam at the end of the course – The last chance for you to catch up