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.