The objective of this research is to develop a new solution approach by combining multiple evolutionary and related algorithms within a population based stochastic search structure for solving constrained optimization problems.
Program Code: 1885
Objectives:
The objective of this research is to develop a new solution approach by combining multiple evolutionary and related algorithms within a population based stochastic search structure for solving constrained optimization problems.
Description of Work:
Studying and analysing the existing evolutionary computation based approaches and traditional optimization techniques for solving constrained optimization problems.
Designing and developing a new solution approach where multiple evolutionary and related algorithms will explore the solution space in parallel by exchanging information at a regular interval.
Analysing the algorithm performance and carrying out the sensitivity analysis of different parameters required by the algorithm.
Solving a reasonable number of well-known benchmark problems and comparing them with the state-of-the-art algorithms.
Skills Assumed:
Knowledge of optimization /operations research /management science and good computer programming skills.
Contact:
Prof Ruhul Sarker r.sarker@adfa.edu.au
School of Engineering & IT