Course Description

Understanding fundamental principles of multi-criterion optimization, definition of different Pareto- optmality conditions, point and population-based algorithms for finding Pareto-optimal trade-off solutions, key multi-criterion decision-making methods. Applications of multi-criterion optimization and decision-making in practical problems from industries and society.

Course Objectives

  • Comprehend the basic principles of point-based classical optimization algorithms and population-based evolutionary optimization algorithms for single-criterion problems.

  • Understand and develop a customized optimization algorithm for a practical problem involving single or multiple criteria.

  • Understand different modes of domination principle and have the ability to define a new and practical one to suit a scenario.

  • Comprehend the basic principles of classical generative algorithms and population-based evolutionary multi-criterion optimization (EMO) algorithms for multi-criterion problems.

  • Know key multi-criterion decision-making methods.

  • Understand ways to integrate multi-criterion optimization and multi-criterion decision-making together to form interactive methods.

  • Know recent advanced topics of research and application in multi-criterion optimization and decision-making.

  • Apply multi-criterion optimization and decision-making methods to practical problems.