888411 Operations Research for Digital Innovation

Lecturer: Dr. Saronsad Sokantika
Email: saronsad.s@cmu.ac.th
Semester: 1/65
Section: 701
Lecture Hour: TuF 8:00-9:30
Classroom: Zoom or ICB1211
Due to Covid-19, every activity in this class will be hybrid. We will use Zoom for online class and use
Microsoft Team for discussion and files distribution.
Zoom ID: 6661420677 or use this link https://cmu-th.zoom.us/j/6661420677

Course Description
Introduction to operation research. Linear programming. Transportation problems. Multi objective
programming. Integer programming. Dynamic programming. Queuing theory. Inventory theory. Decision analysis.
Applications.

Course Objective: Students be able to
1. explain basic theorems in operations research;
2. apply operations research to problems in business management.

Evaluation Criteria Weight
• Presentation 10%
• Homework 30%
• Midterm examination 30%
• Final examination 30%

Presentation
Each student will select one operations research project to make a 5-min presentation on the background of the
project, what is the problem they try to solve, which operations research technique and method they use in this
project, and what is the impact after using operations research.

Grading system
The grade you received can be determined as follows:
Total Scores 100-80 79.99-75 74.99-70 69.99-65 64.99-60 59.99-55 54.99-45 44.99-0
Grade A B+ B C+ C D+ D F

Course outline
Date Topics Hours
21 Jun 22 1. Introduction to Operations Research
• Introduction
• History of Operations Research
• Stages of Development of Operations Research
• Relationship Between Manager and OR Specialist
• OR Tools and Techniques
• Applications of Operations Research
• Limitations of Operations Research

1.5
24 Jun 22 2. Linear Programming – Graphical Method
• Introduction to Linear Programming
• Linear Programming Problem Formulation
• Formulation with Different Types of Constraints
• Graphical Analysis of Linear Programming
• Graphical Linear Programming Solution
• Multiple Optimal Solutions
• Unbounded Solution
• Infeasible Solution

1.5
28 Jun 22
1 Jul 22
5 Jul 22
3. Linear Programming - Simplex Method
• Basics of Simplex Method
• How to use excel solver
• Multiple Solutions
• Unbounded Solution
• Infeasible Solution
• Post optimal analysis
4.5
8 Jul 22
12 Jul 22
19 Jul 22

4. The Transportation and Assignment Problems
• Transportation Problem
• Unbalanced Transportation Problem
• The Assignment Problem

4.5
Date Topics Hours
22 Jul 22
26 Jul 22
2 Aug 22

5. Integer Programming
• Binary Integer Programming
• Mixed Integer Programming
• Branch and Bound

4.5
5 Aug 22
9 Aug 22
16 Aug 22
19 Aug 22

6. Nonlinear Programming
• Type of nonlinear programming
• Linearly Constrained Optimization
• The Quadratic Programming
• Convex Programming
• Separable Programming
• Nonconvex Programming
• GRAPHICAL ILLUSTRATION OF NONLINEAR PROGRAMMING PROBLEMS
• SOLVING NONLINEAR PROGRAMMING BY USING EXCEL
• GRG nonlinear
• Evolutionary
• Adjust Excel Solver Options

6
Midterm Exam
6 Sep 22
9 Sep 22

7. Multi Criteria Decision Making
• Multiple Attribute Decision Making
• Weight sum method
• Weigh product method
• Analytic hierarchy process
• Multi-Objective Decision Making
• Linear Goal Programming
• Pareto Optimization

3
13 Sep 22
16 Sep 22
20 Sep 22
23 Sep 22

8. Network Optimization Models
• Terminology of networks
• The Shortest-Path Problem
• The Minimum Spanning Tree Problem
• The Maximum Flow Problem
6
Date Topics Hours
• The Minimum Cost Flow Problem

27 Sep 22
30 Sep 22

9. Project Management with PERT/CPM
• Visually display a project with network
• Scheduling a Project with PERT/CPM
• Time-Cost Trade-Offs
• Scheduling and Controlling Project Costs

3
4 Oct 22
7 Oct 22


10. Dynamic Programming
• Characteristics of Dynamic Programming Problems
• Deterministic Dynamic Programming
• Probabilistic Dynamic Programming

3
11 Oct 22
14 Oct 22



11. Inventory Theory
• Objectives of Inventory
• Inventory is an Essential Requirement
• Basic Functions of Inventory
• Types of Inventory
• Factors Affecting Inventory

3
18 Oct 22
21 Oct 22
extraclass


12. Decision Analysis
• Decision Making without Experimentation
• Decision Making with Experimentation
• Decision Trees
• Utility Theory

4.5
Final Exam






Additional rules
1. Submission after deadline will be reduce 1 score per day. It is suggested to submit earlier as soon as you
can. Any excuse must be backed up with official document.
2. Any kind of cheating is prohibited and allows no tolerance. Noted that duplicated Copy & Paste is considered as
“cheating”.
3. Common sense applies in any situation. However, if any suspicion persists, do ask earlier.
4. Students must keep evidence by taking photos or screen capture of submission and keep them until the final
exam.
5. Any change in the course after the first class must be made in consensus.
6. Withdrawal of the course could be made before Jan 28, 2022.
7. Lecturer reserves the right to decide whenever any ambiguity arise.