Singapore University of Social Sciences

Linear Optimisation Methods and Applications (MTH310)

Applications Open: To be confirmed

Applications Close: To be confirmed

Next Available Intake: To be confirmed

Course Types: Modular Undergraduate Course

Language: English

Duration: 6 months

Fees: To be confirmed

Area of Interest: Science & Technology

Schemes: Lifelong Learning Credit (L2C)

Funding: To be confirmed


The formulation of optimization models is considered, together with applications, and the various solution techniques widely used to solve the underlying linear objective function under a constrained systems of linear equations. The computer software accompanying this course is used as a powerful tool to solve various linear optmimization models.

Level: 3
Credit Units: 5
Presentation Pattern: Every January
E-Learning: BLENDED - Learning is done MAINLY online using interactive study materials in Canvas. Students receive guidance and support from online instructors via discussion forums and emails. This is supplemented with SOME face-to-face sessions. If the course has an exam component, This will be administered on-campus.


  • Systems of linear equations.
  • Solution space.
  • Formulation of linear programming models.
  • Matrix formulation of simplex method.
  • Principles of the simplex solution method.
  • One-phase and two-phase simplex method.
  • Integer programming models.
  • Solution methods.
  • Applications of linear programming.
  • Integer programming.
  • Optimization problem-solving.
  • Case studies of industrial and applied problems.

Learning Outcome

  • Apply LU decomposition and examine conditions for convergence of solutions of linear systems.
  • Formulate linear programming models. Apply the graphical method to find the optimum solution of two-variables linear programming models.
  • Use the standard one-phase simplex method to solve linear optimisation models.
  • Analyse linear optimisation problems with the two-phase simplex solution technique.
  • Employ the branch and bound method to solve integer programming and 0-1 variable models.
  • Compute the optimum solution of a large linear programming model with the modern interior point method.
  • Construct a range of mathematical techniques to solve a variety of quantitative problems.
  • Formulate solutions to problems individually and/or as part of a group.
  • Analyze and solve a number of problem sets within strict deadlines.
  • Verify solutions related to linear optimisation using Mathcad.
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