Singapore University of Social Sciences

Optimisation and Simulation for Decision-Making

Optimisation and Simulation for Decision-Making (LOG307)

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: Business Administration

Schemes: Lifelong Learning Credit (L2C)

Funding: To be confirmed

School/Department: School of Business


Synopsis

Quantitative models are essential tools in the success of firms in today’s highly competitive and complex business environment. LOG307 Optimisation and Simulation for Decision-Making emphasises on analysing, developing and solving quantitative models to support decision-making focussing on the supply chain. Two main modelling techniques - optimisation and simulation - will be employed to solve complex business problems. The course also addresses decision-making under uncertainty as well as the fundamentals of metaheuristic algorithms. Spreadsheet will be used to construct and solve the models. Through hands-on exercises and cases, the course will equip students with problem-solving and analytical skills as well as enhance their digital fluency in a data-driven environment.

Level: 3
Credit Units: 5
Presentation Pattern: Every January

Topics

  • Introduction to Optimisation and Simulation
  • Linear Programming Problems in Supply Chains
  • Integer Linear Programming
  • Integer Linear Programming Problems in Supply Chains
  • Nonlinear Programming
  • Fundamentals of Metaheuristics
  • Simulation Fundamentals
  • Simulation Tools
  • Simulation Modelling
  • Solving Supply Chain Problems using Simulation
  • Decision-Making under Uncertainty
  • Application of Optimisation and Simulation in Practice

Learning Outcome

  • Apply linear programming models to support decision-making in the industry.
  • Solve integer linear programming models to optimise various business decisions.
  • Appraise the role of nonlinear programming and metaheuristics in solving complex supply chain problems.
  • Analyse different simulation tools for various complex problems.
  • Construct simulation models to solve business problems.
  • Demonstrate how to make decisions under uncertainty.
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