This is an intermediate level module. The module introduces students to a range of Management Science techniques. Emphasis is on application of techniques using a problem scenario approach.
Introduction: The Management Science approach; problem definition, model formulation, data selection, solution, implementation.
Linear Programming : Problem formulation. Graphical solution. Solver solution. Solution interpretation and sensitivity analysis. Applications.
Project Scheduling: Drawing the network. Calculation of event times and floats, determining the critical path. PERT and uncertainty. Resource scheduling and Gantt charts. Crashing and associated costs.
Inventory Management: EOQ model, production lot-size model, quantity discounts, planned shortages. Stochastic models: re-order point with uncertain demand, determination of optimum safety stocks.
Decision Analysis: Structuring the decision problem, pay-off tables and decision trees. Decision rules without probabilities……Minimax, Maximum, Maximax. Decision rules with probabilities……….Expected value approach. Sensitivity Analysis. Decision analysis with sample information and posterior probabilities. Value of perfect information, value of sample information.
Simulation: Building a simulation model. Simulation with stochastic systems, generating random inputs. Simulation of inventory and queuing systems. Decision making. Spreadsheet simulation using Excel
The module will be taught using a combination of lectures, tutorials and laboratory sessions. Course notes and problem sheets will be supplied. Emphasis will be placed on problem recognition , model building, solution determination and decision making. Throughout the module examples and problems from a business environment will be used.
| Module Content & Assessment | |
|---|---|
| Assessment Breakdown | % |
| Formal Examination | 80 |
| Other Assessment(s) | 20 |