Engineering and IT

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:

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:

Objectives:

The objective of this research is to develop a new evolutionary algorithm for solving and resolving job-shop scheduling problems when the production process is interrupted by any internal or external factors.

Description of Work:

Objectives:

The objective of this research is to develop a new agent based evolutionary algorithm for solving multi-objective constrained optimization problems.

Description of Work:

Objectives:

Big data are massive datasets in the order of terabytes and beyond. Scaling up neural networks to datasets of this size is not a trivial task. The objective of this project is to design neural networks that can discover relationships in Big Data efficiently.

Expected Background Knowledge:

  • Knowledge or demonstrated ability to do programming in parallel highperformance computing environment using C or JAVA
  • Good understanding of Neural Networks

Description of work:

Objectives:

Evolutionary algorithms are implicitly parallel search techniques inspired by evolutionary principles. Work in evolutionary algorithms can take many forms including biologically motivated models and statistical modelling of an optimization problem. The objective of this project is to develop decomposition techniques for evolutionary algorithms in optimization and/or machine learning problems. The decomposition needs to be self-organizing, as such, it is not a fixed predefined scheme of decomposition.

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