Overview

Google, IBM & Meta Certificates – 40% Off

One Coursera Plus subscription covers most Professional Certificates on Coursera.

This course introduces fundamental quantitative techniques for optimising business decisions and allocating resources efficiently. It covers Linear Programming Problems and sensitivity analysis, followed by specialised optimisation models such as transportation and assignment problems. The course concludes with decision-making theory, payoff tables, and decision trees for evaluating alternatives under certainty, uncertainty, and risk. Through practical business situations and case studies, learners develop the ability to formulate optimisation problems, analyse solutions, and make informed decisions. By the end of the course, learners will be able to: 1. Formulate and solve Linear Programming Problems to optimise business objectives subject to constraints. 2. Apply sensitivity analysis to evaluate the impact of changes in parameters on an optimal solution. 3. Solve transportation and assignment problems to support efficient allocation, distribution, and resource-matching decisions. 4. Apply decision-making tools, including payoff tables, expected monetary value, and decision trees, to evaluate alternatives under certainty, uncertainty, and risk.

Syllabus

Linear Programming Problems & Sensitivity Analysis
- In this module, you will be introduced to Linear Programming Models (LPP), the core of optimisation systems. The application of this decision-making tool to different types of LPP will aid a decision-maker in a real-world business situation. We will further discuss the post-optimality situation: you will learn how sensitivity analysis can help a decision-maker explore and tackle potential changes in LPP from the optimal solution obtained.
Introduction to Assignment & Transportation Problems
- This week we will discuss three special types of LPP: Assignment, Transportation and Transshipment. Transportation problems are a type of typical Distribution problems where supplies of goods manufactured or stored in various locations (Origins) are to be distributed to receiving locations (Destinations) while optimising the objective of such a distribution task. Assignment Problems, they are essentially a one-one matching pair from one group to another while optimising the objective of such pairing activity.
Fundamentals of Decision-Making Theory & Decision Tree
- This week concludes the course by introducing a general approach to decision theory with two important tools: the payoff table and the decision tree for decision-making. We will discuss Decision-Making in certain, uncertain, and risky situations and its nuances, through a short case study. Through another case study, you will learn how to construct and analyse decision tree, EMV calculations and their implications.