Operations Research: an Active Learning Approach
About this courseSkip About this course
Operations management deals with operational planning and control issues, and is needed in all sectors of the society. One of the challenges to operations manager is how to make use of the available resources in the best way for meeting a certain objective. Quantitative approaches are inevitably needed in tackling many of such problems.
Operations Research (OR) deals with problem formulation and application of analytical methods to assist in decision-making of operational problems in planning and control. The techniques of OR are useful quantitative tools to assist operations managers, and has a wide applicability in engineering, manufacturing, construction, financial and various service sectors.
Operations Research is an applied mathematics subject and is also a course in many engineering and management programmes. This course is designed for both students learning OR and learners who are practitioners in their respective professionals. The mathematical procedures for the OR techniques are introduced in details in the examples provided in the course. This helps learners to master the methodology and the techniques and apply them to achieve their goals through active learning.
This course introduces two prominent OR techniques and their extended topics. The Simplex Method for Linear Programming (LP) has been considered one of the top 10 algorithms of the 20th century. LP is an optimization technique for solving problems such as finding the optimal product mix, production plan, and shipment allocation, in order to maximize the profir or minimize the cost. The Critical Path Method (CPM) is a popular technique employed by project managers in scheduling project activities. Some extended topics of CPM are also introduced to deal with certain special situations in project management.
In reality, many systems operate under stochastic environment and the operational problems cannot be solved by the known analytical methods. To this end, the simulation approach is introduced in the last chapter of this course. Simulation is a powerful technique for tackling OR problems under such situations.
At a glance
- Institution: HKPolyUx
- Subject: Business & Management
- Level: Intermediate
- Knowledge of mathematics at high school level
- Knowledge of probability distributions and statistics, and preferably basic calculus, for learning Simulation
- Language: English
- Video Transcript: English
What you'll learnSkip What you'll learn
At the end of this course, you'll will be able to:
- understand and apply the methodology of Operations Research to investigate and tackle your operational problems;
- formulate and apply the techniques of Linear Programming and the extended topics to solve certain optimization problems;
- apply the techniques of Critical Path Method and PERT in project management;
- appreciate the use of simulation in studying the behaviour of stochastic operations systems;
- and understand the limitations of these techniques.
Chapter 0: Introduction to Operations Research
Chapter 1: Linear Programming and Simplex Method
Introduction to of linear programming (LP) problem, formulating a problem as an LP problem, simplex method in solving maximization and minimization LP problems
Chapter 2: Further Techniques in Simplex Method
Artificial variables in simplex method, M-method, two-phase method, sensitivity analysis, special cases in simplex
Chapter 3: Transportation Problem and Assignment Problem
Introduction and modelling of transportation problem, transportation algorithm, introduction to assignment model, solving assignment problems by the Hungarian method
Chapter 4: Critical Path Method for Project Scheduling
Introduction to project management and network models, network representations for projects, determination of project duration by the critical path method (CPM), using a time schedule in assisting project planning and control
Chapter 5: Further Topics in Critical Path Method
Project crashing, Program evaluation and review techniques (PERT)
Chapter 6: Simulation
Introduction to simulation, generation of random variates, examples of applications of simulation