About the lecturer Dr Qing Lu Henry Grew

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. 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

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

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

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, p 1) 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

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

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

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

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

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

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