Multi-methodology for constrained optimization

Program Code: 
1885
Contact: 

Prof Ruhul Sarker (r.sarker@adfa.edu.au)

Description of Work: 

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.