The objective of this research is to develop a new evolutionary algorithm for solving large-scale multi-objective constrained optimization problems by dividing the tasks and using parallel machines.
Program Code: 1885
Objectives:
The objective of this research is to develop a new evolutionary algorithm for solving large-scale multi-objective constrained optimization problems by dividing the tasks and using parallel machines.
Description of Work:
Studying and analysing the existing evolutionary multi-objective algorithms for solving single and multi-objective constrained optimization problems.
Designing and developing a new evolutionary algorithm for solving largescale multi-objective constrained optimization problems that will allow an intelligent way of dividing the tasks for implementation in parallel machines.
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