Multi-methodology for constrained optimization
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.
Knowledge of optimization /operations research /management science and good computer programming skills.