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.
