Decision 2
Chapter 1  Critical Path Analysis


Representation of compound projects by activity networks, algorithm to find the critical path(s); cascade (or Gantt) diagrams; resource histograms and resource levelling.

Activityonnode representation will be used for project networks. Heuristic procedures only are required for resource levelling.
Candidates may be
required to comment on the appropriateness of their solution in its
context 
Chapter 2  Allocation


The Hungarian algorithm. 
Including the use of a dummy row or column for unbalanced problems. The use of an algorithm to establish a maximal matching may be required. 
Chapter 3  Dynamic Programming


The ability to cope with negative edge lengths. Application to production planning. Finding minimum or maximum path through a network. Solving maximin and minimax problems. 
A stage and state approach may be required in dynamic programming problems. 
Chapter 4  Network Flows


Maximum flow/minimum cut theorem.

Problems may require supersources and sinks, may have upper and lower capacities and may have vertex restrictions. For flow augmentation.

Chapter 5  Linear Programming


The Simplex method and the Simplex tableau. 
Candidates will be expected to introduce slack variables, iterate using a tableau and interpret the outcome at each stage. 
Chapter 6  Game Theory for Zero Sum Games


Payoff matrix, playsafe strategies and saddle points. Optimal mixed strategies for the graphical method. 
Reduction of payoff matrix using dominance arguments. Candidates may be required to comment on the appropriateness of their solution in its context

Chapter 7  Mathematical Modelling


The application of mathematical modelling to situations that relate to the topics covered in this module.

Including the interpretation of results in context. 